- Private group -

GSS addresses new ways of supporting policy decision making on globally interconnected challenges such as urbanism and migration, environmental issues and climate change, financial crises, or containment of pandemics. The ICT engines behind GSS are large-scale computing platforms to simulate highly interconnected systems including cross-cutting policy dependencies and interactions, data analytics for 'Big Data' to make full use of the abundance of high-dimensional and often uncertain data on social, economic, financial, and ecological systems available today, and novel participatory tools and processes for gathering and linking scientific evidence into the policy process and into societal dialogue. GSS will develop further the scientific and technological foundations in systems science, computer science, and mathematics.

What are we looking for?
•    What should be the orientation of research on this topic? As stated, do you feel it is too broad or, on the contrary, too narrow?
•    Have any recent scientific results been obtained relevant to this topic? Is there already a well-established community on this?
•    Do you know of related initiatives, for instance at national level, or in other continents?
•    What is needed at this point to advance this? More exploration of different ideas? More coordination among groups or related initiatives? A strong push for a precise technological target and, if so, which one? Anything else?

Background: Following the last FET consultation during 2012-13, 9 topics were identified as candidates for a FET Proactive. This topic has been selected for inclusion in the FET Work Programme for 2014-15. Comments are invited on whether this topic is still relevant, or if any changes would be necessary to take account of recent research results. We are also trying to understand better how to advance these areas.

To participate to the consultation:
- register to the group (create an ECAS login if you don't have one yet);
- then "log in" and enter your contribution in the "Add new comment" box, at the vey bottom of the page.
You can also participate by commenting on submitted ideas and/or voting for them.

If you wish to share with us additional documents or have any questions about the process, please send them to our FET mailbox.

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nfentosi's picture

Global Networks

Hi Beatrice,

I think we can progress here if we focus, not on ICT, But Networks. That said, we have every National Research and Education Network manager attempting to interconnect. I'll just point at the conference materials for two of the largest continental associations. and

So here's the conundrum. The EC and nsf, and other funders, will fund these network managers, and various projects that will use and try and develop global interconnections, individually. And you can see the result. They, individually, will get together in rooms, scattered around the world, at different times, and talk about building global networks. So we get the great irony that, because they are funded individually, they will only compare what each silo is doing. They will never collaborate.

Let me illustrate just how silly this gets. We have people from around the world, who aspire to developing global networks, getting together in a little room F2F. Then they will do the same at other conferences, at a different time, in a different place, and bury their GROUP's ( I emphasize the point) conference materials on various web sites.

These comms managers have at their fingertips some Communication tools which would have every EC/nsf communications manager salivating. Video conference, video streaming, mini TV stations. You name it, their networks can provide it. Now, apart from scattering their group's recordings/presentations/reports all around different domains, (which is no way of sharing an ongoing global education) they end up using a toy like Skype. One couldn't make this up :) And this is no isolated incident. This is the way all institutions behave.

So the Catch 22 continues. (Groups of) Funders don't have the kind of global networks which will enable them to fund the building of global networks. Your approach here, in splitting the conversation into groups, is no different than any other institutional inquiry. Your peer groups are buried inside the domain just like every institution, because they've been funded on an institutional basis. And insiders and outsiders can share the same network services/apps by using ecas, like all groups must do when accessing some institutional network. That's why we/they all suffer the million password syndrome.

So let me just point to two presentation that will be given at terena's conference.
The second one is important as it focusses on the primary change in building global networks.
"3. Group provider centric, i.e., the attributes are provided by a group provider."

The challenge now is to see if we can't get you peers in other funders to share the same GROUPS directory. (e.g. and ) and services. If we can do that we can start developing some global networks.

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ntabarjd's picture

GSS is about interlinking Global Solutions

Dear all,

I just want to remind, as one of the authors who contributed to the first Orientation Paper on GSS, an essential way to frame and communicate the crucial importance of GSS which could be of help to move forward with it in some instances. In particular, in my view, GSS can be seen as one of the most robust ways to identifying and assessing 'systems of interlinked solutions to global problems', of course with the help of new -largely distributed- IT and computer technologies. Hence, GSS is indispensible to avoid the exponential multiplication of global problems derived from non-systemic, partial and short-term solutions to collective problems occurring in an increased interconnected world. At the moment we don't really have anything to help us mapping, quantifying and connecting that in a scientific way, despite the severity of the global challenges keeps on intensifying.

To discuss these issues we are organising the III Open GSS conference to be held simultaneously in Europe, US and China on the 8-9 (US & Europe) and 9-10 October 2014. Further information, including the procedure on how to submitt posters and abstracts, will be posted in the GSS blog and portal in the coming days ( ), But for the time being I just wanted to share the preminary program with you. (In Europe the event will take place in Brussels, at the EC premises in Berlaymont)

J. David Tabara (Global Climate Forum:


Hosted by:

Arizona State University
Development Research Center of the State Council
of the People’s Republic of China
Global Climate Forum

October 8-10, 2014

Global Systems Science (GSS) is about providing global systems of interconnected solutions to global problems. This involves not only looking at the whole of our planet and its societies, but also looking at it from a transdisciplinary and transformative perspective that connects all kinds of scientific knowledge, and engaging as many people as possible in collective action. The concept of green growth has been proposed as one of the few globally distributed, innovative and engaging systemic solutions to our current global predicament.

The ICT revolution that is currently ongoing will fundamentally reshape our societies, economies and institutions, as well as our environment. The current moment is therefore the right one to reflect on the kind of future we would like to see ahead of us, and the role of ICT in implementing a vision of a global sustainable society.

The future of global economic growth raises a whole range of questions, including, but not limited to, purely economic ones. Will the successes in reducing global poverty continue? Will inequality within key economies continue to increase? Will global and local environmental disruption continue? In the face of these questions, green growth has been proposed as an appropriate strategy. The vision of billions of poor people achieving a decent standard of living while economic activities become a force of environmental enhancement rather than disruption is certainly attractive. But is it feasible? What experiences have been made so far? What obstacles, what risks should be expected? What alternatives do exist?

On October 8-10, scholars and practitioners will meet in the US, China and Europe to share insights and discuss open questions about green growth. The three sub-events will be connected via Internet, and the conference as a whole shall help to develop the research needed to address global challenges like the one of green growth. The American and European sub-events will be held on October 8-9. The Chinese sub-event will be held in a scenic rural region during October 9-10 with a separate one-day sub-event on October 8 in Beijing.

Call for Papers and Posters

The overall conference will be structured roughly according to the following eight topics, each one with two sub-topics. Authors are encouraged to submit abstracts for papers or posters that reflect these topics and offer a significant contribution to the trans-continental discussions. At the present stage, this structure is relatively flexible to accommodate needs and opportunities that may arise in the coming months. Depending on papers and posters submitted and accepted, particular topics will be discussed in one, two or three of the locations of the conference.

1. Environment
- Complexities of climate policy
- Challenges of air pollution
The very notion of green growth answers to the reality of global environmental change and the risks that it engenders for the future. By focusing on climate change and air pollution, the conference shall foster research about the interaction between short and long term and between local and global problems.

2. ITC as a game changer
- Big data and high performance computing
- Social media and civil society
The rise of information technologies is changing the way we process material objects, the way we generate and use energy flows, and of course the way we gather, store and process data about all kinds of situations. Doing so in an effective way can open up major opportunities of green growth, not only in view of resource use, but also in view of making better individual and collective decisions about problems of global relevance. However, there is a great need to explore and realize these possibilities while being aware of the related pitfalls.

3. Green business models
- Material goods and energy
- Information services
Businesses experimenting with or actually implementing green business models find increasing attention in the media. However, little solid empirical evidence about their experiences is available, and theoretical analyses in the literature are full of unresolved conflicts. Clearly, research is warranted on this topic. It is obviously very important for businesses dealing with material goods and energy, but increasingly the role of information services nees to be investigated in view of the possibility of global green growth.

4. Pitfalls of green growth
- Greenwashing
- New inequalities
History is full of failures and disasters brought about in the name of lofty ideals. As with other global problems, we need an open conversation about green growth with plenty of space for critical analysis. Two kinds of critiques may be distinguished: on one hand there are analyses focussing on situations where green rhetoric is used to create mere illusions of sustainability, on the other hand there are those focussing on situations where green growth policies end up – perhaps unintentionally – worsening the situation they were supposed to improve. The latter issue is especially sensitive in view of the dynamics of inequality at different scales.

5. Sustainable finance?
- Measuring systemic risk
- Global financial governance
So far, the conversations about financial risks and the one about sustainability ake. develop largely separated from each other. This is unfortunate for many reasons. E.g., financial risks and the risks usually associated with sustainability show a similar pattern: short-term risks are often addressed by postponing them into a more distant future, often raising the stakes. Against this background, research about how to identify and measure systemic risks on financial markets may be relevant for other kinds of risk, too. And discussions about global financial governance should not be kept separate from the question of what kind of growth the world economy will experience in the 21st century.

6. Theory and models
- Beyond marginalism
- Enhancing the modeling toolbox
The literature on green growth illustrates a point of much broader relevance in the study of global problems: there is no really solid theory about these problems. In view of green growth – and of many other problems – the most influential theoretical approach is the marginalist one. In this approach, one focusses on marginal changes, studies the trade-offs they involve and then extrapolates these to much larger scales. While this is often appropriate, there is an urgent need to go beyond marginal analysis when thinking about such a profound shift as the one implied by the notion of green growth. Given the importance of simulation models for today’s policy debates, this is related to the challenge of enhancing the presently available modeling toolbox.

7. Regional dynamics
- Opportunities for rural regions
- Futures of urban systems
Ultimately, the future of green growth hinges on a whole set of global coordination problems. For a start, however, - positive and negative - experiences of green growth seem to be made mainly at the regional level. A key question is whether peripheral, rural, poor regions can realize new opportunities in a green growth perspective, e.g. by combining advanced information technologies with a new valorization of landscapes that inhabitants of urban regions may perceive as precious resources. A complementary question is how the majority of humankind that will live in urban agglomerations in the coming decades can do so in a sustainable and satisfying way. Case studies, broader empirical analyses and theoretical advances are all needed to address these questions.

8. Transition governance
- Governments and international institutions.
- Other actors and transnational complexes
Managing the transition towards a more sustainable pattern of global development is a daunting task. Governments and international institutions formed by them will play an essential, but certainly not sufficient role in this process. Examining their potential and limitations, especially in avoiding major conflicts and securing non-trivial levels of fairness, is a key research task. An indispensible, complementary task is to investigate how other actors - businesses, media, academic institutions, NGOs and many more - can contribute to transnational governance complexes addressing challenges and pitfalls of green growth. This need not be limited to actors existing today; at least as important will be enquires into new kinds of organizations that may contribute to an environmentally, economically and - last but not least - socially successful sustainability transition.

Submission of Abstracts

Electronic submissions of abstracts for papers and posters (300 words maximum) will be through EasyChair (link available in the coming days)

The official language of the conference at all three locations is English. Please submit abstracts in English.

Abstracts will be reviewed and accepted according to their order of submission and relevance to overall conference objectives. Authors of accepted abstracts will be invited to participate at the conference location nearest to their place of work and residence. There will be no conference registration fees for presenters. Presenters will be responsible for their own travel and lodging. There may be a limited number of small travel grants for presenters who express need. Papers at the conference will be presented in a short oral version while the text will be available over the internet at all locations.

Posters at the conference will be presented electronically (pdf file format) and available over the Internet at all locations. Upon acceptance of the abstract, poster authors will be provided additional information on preparation of the poster for electronic presentation. The abstract should articulate the objectives of the presenter, a brief but thorough description of the research, and the expected gain by those attending the talk. When submitting an abstract, please identify your first and second choice of topics that best represent your work from the following list:

Overview of the conference topics:

- Complexities of climate policy
- Challenges of air pollution
ITC as a game changer
- Big data and high performance computing
- Social media and civil society
Green business models
- Material goods and energy
- Information services
Sustainable finance?
- Measuring systemic risk
- Global financial governance
Theory and models
- Beyond marginalism
- Enhancing the modeling toolbox
Theory and models
- Beyond marginalism
- Enhancing the modeling toolbox
Regional dynamics
- Opportunities for rural regions
- Futures of urban systems
Transition governance
- Governments and international institutions
- Other actors and transitional complexes.

Important Dates

June 15, 2014: Deadline for submission of abstracts of papers or posters.

July 15, 2014: Acceptance/Rejection notification.

September 15, 2014: Final abstracts due in electronic form. Accepted abstracts will be distributed to the conference participants, as will complete papers if submitted by that date.

September 15, 2014: Final posters due in electronic form. Accepted posters will be available on the Internet to the conference participants.

Review process
All submissions will be peer reviewed by at least two reviewers. Reviewers will be accepting only those abstracts that indicate high quality theory and research and are consistent with the objectives of the conference.
Conference Global Organizing Committee
Zhangang Han (Beijing Normal University)
Carlo Jaeger (Arizona State University)
Ulf Dahlsten (former EC Director and Global Climate Forum)
Yanli Lue (Beijing Normal University)
Antoine Mandel (Université Paris)
Diana Mangalagiu (University of Oxford)
Jahel Mielke (Global Climate Forum)
Franziska Schutze (Global Climate Forum)
Gesine Steudle (Global Climate Forum)
Joan David Tabara (Autonomous University of Barcelona)
Sander Van Der Leeuw (Arizona State University)
Saini Yang (Beijing Normal University)
Qian Ye (Beijing Normal University)
Yongsheng Zhang (Development Research Centre, PRC)


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njohnjef's picture

The NESS 2014 GSS Roadmap

THE NESS (Non-Equilibrium Social Science) coordination action is working on a roadmap for GSS to be published at the end of 2014, following on from the work done and roadmap of GSDP (Global System Dynamics and Policy). We welcome the widest possible participation and will try to represent the views of everyone. For more information contact

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nbattisn's picture

Example of Policy Application of Global System Science

Dear all,

We would like to comment on ax example of application of Global Systems Science for policy.

As part of the projects SIMPOL and FOC we have been working a lot on systemic risk in collaboration with central banks and other regulatory bodies. This months we were co-organizing a conference at the International Monetary Fund about the role of interconnectedness in financial networks. Here are the links to the conference page
and summary that was issued after the conference

The topic of interconnectedness is an important one because the policy discourse before the crisis was focused on the benefits of having a more interconnected financial system. This type of theoretical arguments were behind the wave of liberalization and deregulation that charaterized the years from early 90 until 2007. Therefore, the practical implications of this discussion cannot be overstated since they were a fundamental ingredient of the toxic mix that lead to the current economic situation.

A growing stream of research, to which FOC and SIMPOL have been contributing, has shown when and why interconnectedness is dangerous, thus contributing to create a different set of narratives among policy makers.

More in general, the vision emerging from the work of FOC and now from SIMPOL is that we have today concrete ideas on what to do with systemic risk, but that what prevents us to put them in place is a political dimension, namely an issue of economic interests that are too concentrated (moral hazard and Too-big-to-fail) and a coordination problem. These ideas have been elaborated thanks to the teaming up of network scientists, economists and policy makers and they are completely in line with the spirit of Global Systems Science.

In essence we argue that as a result of Global System Science approach policy we should put in place incentives to reduce *at the same time*: interconnectedness, correlation and complexity of instruments. Notice that, thanks also to our contribution, a similar point of view have emerged in the IMF conference mentioned above.

We report here below the discussion the Stefano Battiston and Guido Caldarelli have recently tried to summarize in a review paper on the topic. The full text is available at

Stefano Battiston (SIMPOL & FOC) & Guido Caldarelli (FOC & MULTIPLEX)

Most macro-prudential policies for financial stability focus on individual bank ratios such leverage or capital adequacy ratios or equity ratios. Then, in terms of assessing the systemic importance of the various institutions, most of the attention has been on bank size. The dimension of interconnectedness (meant as amount of exposures on the interbank market) has been included (along with others) in the IMF/BIS/FSB report submitted to the G20 Finance Ministers and central bank Governors in October 2009. Moreover, the Basel Committee on Banking Supervision (2013) has recently suggested to include the dimension of complexity, as a measure of the cost of resolving the bank, which depends on the amount of notional OTC derivatives held by banks.
In the context of such debate, three interrelated dimensions play a major role in the analyses presented earlier: interconnectedness, complexity and correlation.
As we have seen earlier, in the model of default cascades higher interconnectedness leads to higher systemic risk when coupled with illiquidity and low capital buffers. The DebtRank method also shows that a higher interconnectedness among banks increases the systemic impact of each bank over the others. In particular, if a bank keeps its amount of exposures and diversifies them over a larger number of counterparties, this is beneficial for the individual bank as it reduces the loss from any single counterparty. However, such diversification increases the chances that the bank will act as channel to spread the distress from a shocked bank to a third one. Overall, a fully connected network spreads around more distress than a sparse network.
More in general, besides the interconnectedness arising from the interbank lending, it is useful to think of the interdependence of balance sheets and payoffs of banks arising from various financial instruments. A general insight from the study of financial net- works is that interdependence is a source of systemic risk, as soon as positive feedbacks are present in the system (Battiston et al., 2012a). Now, positive feedbacks are very often present in financial markets, either visible or latent. An example is the procyclical spiral fire-selling-asset devaluation, which can be triggered by a change in agents’ expectations on the future value of that asset. Clearly this can also be seen as an effect the potential illiquidity of the market for assets. Another example is the fact that the very reaction of creditors (e.g. tightening credit conditions) to a first deterioration of an obligor’s equity ratio, is likely to induce its further deterioration. This is also a manifestation of a positive feedback. In the natural sciences, a system where positive feedbacks prevail is prototypical of a unstable system. If its units are also highly interdependent it is immediately recognized as prone to systemic risk.
The complexity of banks may well be seen as to contribute to their interdependence, due to the OTC derivatives contracts that a bank establishes with others. The argument that these contracts help to diversify and reduce risk is controversial (Battiston et al., 2013). While the dimension of complexity did not appear directly in the models presented above, the complexity of financial instruments is likely to contribute to the potential illiquidity of the market. Indeed when players start questioning the value of an asset, its complexity is not of help in making counterparties willing to buy it. Another problem of complexity is that it makes room for information asymmetries that in bad times can be exploited by market players as an argument for being too complex-to-fail (Battiston et al., 2013). This exacerbates the effect of the findings from the DebtRank method where in times of low capitalization all banks become systemically important.
Finally, the correlation of banks’ behavior is another important dimension that indirectly contributes to the potential for market illiquidity. Clearly, the more banks have made correlated choices in their portfolio, the stronger will be the effects when they all try to fire-sell the same type of asset.
Overall, in our view the literature suggests that in order to contain systemic risk, besides maintaining capital ratios, it is necessary (but maybe not sufficient) to decrease simultaneously the interrelated dimensions of interconnectedness, complexity and correlation. It remains an open and question how to achieve this objective. For instance, it is challenging to design mechanisms to contain interconnectedness and correlation. However, in our view, the various proposals to reform the structure of banks and the architecture of the financial system should be first tested against their ability to deliver progress in this direction. As an example, splitting banks in commercial and investment arms does not, per se, prevent the investment arms of various banks to remain too much connected, complex and correlated. Even if balance sheets of the two arms are virtually separated, once this compartment of the financial system gets in trouble, the distress will propagate to the commercial arms by some other channel. As an urgent future avenue of research, we advocate a thorough comparison of different proposals with respect to those three dimensions as a prerequisite for a more informed debate.

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nmandeai's picture

GSS as a research community

Hi Beatrice,

I would like to share my impression about the emerging GSS community and some of the challenges it adresses that can make a big difference for European citizens.

To start on a personal, note GSS offers me the grand challenges I was looking for when I decided to become a researcher in order to have a positive impact on social organization through quantitative methods. The community is extremely interdisciplinary, allows one to develop tools and methods that are at the research frontier both in ICT and social science and encourages contacts with stakeholders and policy-makers. In this respect, the EU research policy is very well complemented by a range of private and public initiatives such ad the Institute for New Economic Thinking, the New Approaches to Economic Challenges initiative of the OECD or UNEP's financial initiative. This allows young researchers like me to get in contact with leading scientists, policy-makers and NGOs that share the same concerns about global sustainability on the one hand and economic and financial instability on the other hand.

I think the orientation paper on Global System Science edited by Carlo Jaeger, Patrik Jansson, Sander van der Leeuw, Michael Resch and J. David Tàbara gives a great overview of recent results and current challenges for global system science. Let me just highlight one example I am currently working on. There is today a major gap between the investment needs to finance large-scale mitigation of greenhouse emission gases and the demand for environmentally responsible investments that financial institutions seem unable to match by an adequate supply. In the SIMPOL project we are investigating the climate finance networks in order to understand how to fill the structural holes that prevent this necessary flow of funds. To address this issue, we need to bring together insights form network science, finance, environmental policy and integrate them via cutting-edge simulation methods. For me, this is only possible thanks to GSS.

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ncaldagi's picture

Global System Science and Policy

In this new world where people work, communicate, travel, in an unprecedented way, also policy makers need new instruments to describe, forecast and possibly control social and economic phenomena.
These new instruments in my view must be based on the mathematic of graphs/networks and by using the data provided by the various ICT structures.
As an example I want to mention one topic on which we are working on. Queries ( present relevant information on the future volumes of trading.
Of course to extract such an information, different expertise are necessary. This is only one example of the challenges (theoretical and practical) that researchers must face.
For this reason a new generation of researchers is needed, they will need the modelling skills of statical physicists, a good knowledge of discrete mathematics, graph theory and algorithimcs, and finally the skills of computer scientists to handle a deluge of big data. Given the complexity of this task, we cannot think that policy makers could do this analysis on their own. It is therefore necessary to customize software platforms and modelling software to support them

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nkiddkpu's picture

Global Systems Science, Art, RRI and Behavioural Issues

Global Systems Science is self-evidently an important topic, but it is too narrowly conceived and needs to be broadened to become what I call a non-mechanistic and non-reductionist approach to science (it is not just a means of supporting policymaking). It is in this area, which can be called the reinvention of science, that the true potential of GSS will be realised.

GSS also needs to move beyond being interdisciplinary, to become transdisciplinary. It also needs to be founded on a better understanding that all actors involved in GSS are not as they might think, entirely rational, objective, and focused on evidence. There are important behavioural understandings that need to be incorporated into GSS, both in terms of those who practise GSS, and with regard to the subject matters that GSS addresses.

GSS also needs to be revised to take account of the H2020 Responsible Research and Innovation (RRI) agenda. Again this is relevant to both GSS itself and the subject matters that it addresses. The means to address all five pillars of RRI should be explicitly built into the approach, and not just left to individual research projects to consider, which on the whole they will not, as RRI, to be realistic, is not on most people’s agenda, and few people truly understand it. RRI needs to become an explicit part of any GSS process or method.

GSS is also an area where artists should be integrated as key players, for this group of researchers are already exploring the above issues and one can say, transcending traditional disciplinary boundaries. Artists are at core, people who are constantly questioning that which others rarely think about, such as the relevance of science, as it is now, and ways in which it can be developed into something more sophisticated in terms of method and process. This is the value of art, for it offers different ways of seeing the world. And GSS is one area that needs to be seen differently.

I have more to say about GSS, art, and art’s role in FET and GSS, as well as the importance of Time for Time in a GSS context. All this I have explored in my input to the FET Proactive Time for Time consultation (, which I now invite you to read.

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nserferm's picture

GSS - Collective Intelligence - Citizen Science

It is already said here, so I want to endorse this position. Billions of people inter-connected may solve current global challenges in a collective manner by a) contributing with individual solutions b) selecting and evaluating existing approaches c) re-using and adapting others work; leading to the digitally-enabled evolution of emergent intelligence. It is a great challenge to conduct large-scale experiments in order to collect big-user-generated-data with the aim of model and conduct these complex behaviors.

In this sense, the citizen science approach, which is based on the contributions and collaborations of the general public with expert researchers, is fostering the trusted relationships required between all the societal actors. Therefore I suggest FET-GSS to include in its roadmap the recommendations that we will publish in the White Paper on Citizen Science for Europe, which we are creating as part of the Socientize EU-funded project, after the online-offline consultation of all the citizen science community actors.

These consultations are examples of complex challenges, and we usually see how hundreds of individual-bottom-up ideas arise. The development of new and open disruptive brain-based technologies and frameworks for the emergence of collective solutions should be also considered.

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nyamirmo's picture

GSS and Multilevel Systems

I think that Global Systems Science is the right approach to many of the problems we face today. I agree with the previous comments by colleagues and would like to comment on a different aspect, perhaps influenced by my own research work.

For those that do research on complexity, it is becoming more than evident that the most challenging societal problems can only be tackled if we deal with the multilevel and interdependent nature of social, technological and economical, including financial, systems. To this end, projects like MULTIPLEX (funded by a FET Proactive initiative) are making significant contributions to subjects like multilevel and multilayer systems. The idea, that a priori is simple, is to consider that whenever you have more than one interacting system, the interdependency between them should be taken into account if you aim at a better understanding of the dynamics (functioning) of the global system. This principle permeates all fields mentioned above: social systems are made by many different layers in which we all interact, in general, in different ways and with different people, technical systems depend on the functioning of each other, and finally, economical and financial systems are tightly connected to each other. Another example is given by a system as complex as a city: you have different transportation modes defining mobility patterns, which in turn has a great impact on processes such as disease spreading, optimal distribution of resources and facilities, etc.

All the above examples constitute by themselves fantastic scientific challenges. Imagine then tackling all of them concurrently and with as much details as possible. This is precisely what GSS aims at, and that is the reason why I think this initiative should be extended and renovated. Otherwise, we will have closed the doors halfway, preventing the current advances to turn into significant technological and scientific breakthroughs.

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nfagiogi's picture

GSS and Macroeconomics

Hi, Beatrice, I would like to make a brief comment on how Global Systems Science can shed light on important macroeconomic issues related to the interplay between human mobility, international trade, and country performance.

Our recent work on International Migration Networks (IMN, see Fagiolo and Mastrorillo, 2013) has shown that describing migration data using a complex-network representation allows one to capture the complexity of international migration linkages between countries and gives one the possibility to study migration from a systemic perspective, where both direct and indirect linkages are taken into consideration.

Furthermore, knowledge of the IMN structure can explain the patterns of trade among world countries. In particular, in a recent paper appeared in PlosOne (Fagiolo and Mastrorillo, 2014) we ask whether the centrality of countries in the IMN explains, in addition to bilateral-migration effects, their bilateral trade. We find that pairs of countries that are more central in the IMN also trade more. Interestingly, we find that also inward third-party migrants coming from corridors that are not shared by the two countries can be trade enhancing, in addition to common inward ones. We suggest that this can be due to either learning processes of new consumption preferences by migrants whose origins are not shared by the two countries (e.g. facilitated by an open and cosmopolitan environment) or by the presence in both countries of second-generation migrants belonging to the same ethnic group.

In a complementary research project, instead, we ask whether the level of integration of world countries in the international network of temporary human mobility can explain differences in their per-capita income and labor productivity (Fagiolo and Santoni, 2014). We disentangle the role played by global country centrality in the network from traditional openness measures, which only account for local, nearest-neighbor linkages through which ideas and knowledge can flow. Using 1995-2010 data, we show that global country centrality in the temporary human-mobility network enhances both per-capita income and labor productivity. Our results hold cross-sectionally, as well as in a dynamic-panel estimation, and take into account potential endogeneity issues. Our findings imply that how close a country is to the theoretical technological frontier, depends not only on how much she is open to temporary human mobility, but mostly on whether she is embedded in a web of relationships connecting her with other influential partners in the network. Our exercises also suggest that most of the gain in income and productivity can be attained if country centrality in the network comes mostly from influential partners that lie not too far away from, but neither too close to them in the network.

All these examples stress the importance to take a GSS view to macroeconomics, in terms of both positive analysis and policy implications.

- Fagiolo, Giorgio and Santoni, Gianluca (2014) “Human-Mobility Networks, Country Income, and Labor Productivity”. Available at SSRN eLibrary (

- Fagiolo, G. and Mastrorillo, M. (2014) “Does Human Migration Affect International Trade? A Complex-Network Perspective”, PLoS ONE 9(5): e97331, available at:

- Fagiolo, G. and Mastrorillo, M. (2013), “International migration network: Topology and modeling”, Physical Review E, 88, 012812. Available at:

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nfagigio's picture

GSS and the Relation between Inequality, Credit and Crises

Dear Beatrice, we would like to discuss how to employ GSS tools in general, and agent-based modeling in particular, to address global policy issues concerning the relation between inequality, credit and macroeconomic crises.

In a series of papers co-authored with Andrea Roventini, Giovanni Dosi, Mauro Napoletano and Tania Treibich (2010, 2013, 2014) we argue that one of the most lively debates in macroeconomics nowadays focuses on the ability of standard macroeconomic models to forecast and explain the current economic crisis, and to provide ready-to-use policies which could restore growth, curb unemployment (see among many others Dosi, 2011; Krugman, 2011; Stiglitz, 2011) and stop policy makers navigating by sight (Blanchard et al., 2013).

The debate has been raging not only among economic theorists and policy makers, but it has spilled over in newspapers and magazines (see e.g. the article on the state of economics appeared in The Economist, and the following reply of Robert Lucas).

A key point in this discussion concerns the ability of existing (mainstream) models to properly address issues such as heterogeneity and interactions, which are considered central ingredients to understand economic crises as emergent, endogenous phenomena.

In his opening address at the ECB Central Banking Conference 2010, Jean-Claude Trichet, the former president of the ECB, notes that “the atomistic, optimizing agents underlying existing models do not capture behavior during a crisis period. We need to deal better with heterogeneity across agents and the interaction among those heterogeneous agents.” Furthermore, he proposes a possible solution to this problem: “Agent-based modeling dispenses with the optimization assumption and allows for more complex interactions between agents” (Trichet, 2010).

Building on these ideas, our research attempts to fill this gap and employing agent-based models (Tesfatsion, 2006) to explore the properties of macroeconomic dynamics during normal and crisis times (Dosi et al., 2010, 2013, 2014).

We have developed a family of agent-based models that investigate two key issues in the current economic debate: i) the role of increasing income inequality as one of the triggering factors of the crisis (see e.g. Kumhof and Rancière, 2011; Bordo and Meissner, 2012; Stiglitz, 2012); (ii) the short- and long-run impact of monetary and fiscal policies. Two key features of our agent-based approach are that agents are heterogeneous and that markets (e.g., the labor market) do not always clear at any point in time. In this framework, the statistical relationships exhibited by macroeconomic variables should therefore be considered as “emergent properties” stemming from microeconomic “disequilibrium” interactions. Moreover, agents’ behavior is rooted in micro empirical evidence, thus providing an explicit “behavioral” microfoundation of macro dynamics (Akerlof, 2002). The robustness of such empirically-grounded approach is then checked against its capability to statistical account, jointly, for a large set of empirical regularities both at the micro and macro levels.

The basic theoretical framework (Dosi et al., 2013) portrays an artificial economy composed of capital- and consumption-good firms, a population of workers, a bank, a Central Bank and a public sector. Capital-good firms perform R&D and produce heterogeneous machine tools. Consumption-good firms invest in new machines and produce a homogeneous consumption good. Firms finance their production and investment choices employing internal funds as well as credit provided by the banking sector. The Central Bank fixes the interest rate and determines the credit multiplier. Finally, the public sector levies taxes on firm profits and worker wages, and pay unemployment benefits.

The model thus combines a traditional “Keynesian” mechanism of aggregate demand generation with a “Schumpeterian” innovation-fueled process of growth. These two dynamics are in turn nested into an endogenous credit dynamics. In the model, higher production and investment levels rise firms’ debt, eroding their net worths and consequently increasing their credit risk. Banks, in turn, tighten their credit standards. This increases the level of credit rationing in the economy and forces firms to curb production and investment, thus setting the premises for economic-activity slumps.

In general agent-based models do not lend themselves to analytical solutions. Therefore, their properties must be analyzed via extensive computer simulations, which we perform via a three-step strategy. First, we empirically validate the model, i.e., we assess whether the statistical properties of artificially generated microeconomic and macroeconomic data are similar to the empirically observed ones for a large range of model parameters. Second, we explore the role of income inequality as a source of instability at the aggregate level. Third, we use the model as a sort of policy laboratory, exploring the short- and long-run effects of different fiscal and monetary policies under different income distribution scenarios.

We find that the model matches a long list of macro empirical regularities (e.g. persistent output growth, output volatility, co-movements between macro variables, etc.) as well as industry-level stylized facts (e.g. about firm size and growth-rate distributions, firm productivity dynamics, firm investment patterns, etc.). Furthermore, our results show that economies where the profits share is relatively high are more exposed to severe business cycles fluctuations, higher unemployment rates, and higher probability of crises.

On the policy side, simulation exercises reveal the strong interactions between fiscal and monetary policies on the one side, and income distribution on the other. Fiscal policies do not only dampen business cycles, reduce unemployment and the likelihood of experiencing a crisis. In some circumstances, they are are also able to affect long-term growth. The effectiveness of fiscal policy is strictly linked to income inequality: the more income distribution is skewed toward profits, the greater the effects of fiscal policies.

Conversely, on the monetary policy side, we find a strong non-linearity in the way interest rates affect macroeconomic dynamics. More specifically, there exists a threshold beyond which increasing the interest rate implies smaller output growth rates and larger output volatility, unemployment and likelihood of crises. Also the impact of interest rate policies is affected by income distribution: changes in interest rates have a mild impact in less equal economies, because higher profit rates allow firms to be relatively more independent from bank credit. Similarly, the sensitivity of real variables to policies affecting credit multipliers falls with higher profit margins.

We draw two main lessons from our exercises.

First, from a policy perspective, simulation results support the view that income inequality is a potential cause of economic instability: economies where income inequality is higher are also more prone to crises. In addition, they strongly support the idea that counter-cyclical fiscal policies are a necessary condition to keep the economy on a “virtuous” high-growth path. Needless to say, if there is some truth in our conclusions they run exactly counter the current European recipes: the recent fiscal austerity programs pursued by EMU countries are likely to worsen the state of the economy, further lowering the rate of growth, and increasing the instability of European economies.

Second, from a methodological perspective, the whole exercise suggests the very possibility of providing alternative theoretical tools to policy makers, which are firmly grounded in a GSS approach to social sciences, and can endogenously account for crisis emergence within a general disequilibrium macroeconomic-dynamics rooted in an explicit empirically-grounded microfoundation of interactions and individual behaviors.


AA.VV., 2009. The Other-Worldly Philosophers. The Economist. July, 16th, .

Akerlof, G. A., 2002. Behavioral Macroeconomics and Macroeconomic Behavior. American Economic Review. 92, 411–433.

Blanchard, O., Dell’Ariccia, G. Mauro, P., 2013. Rethinking Macro Policy II: Getting Granular. IMF Staff Discussion Note SDN/13/03. IMF.

Bordo, M. Meissner, C., 2012. Does inequality lead to a financial crisis? . VoxEU. 24 March.

Dosi, G., 2011. Economic Coordination and Dynamics: Some Elements of an Alternative “Evolutionary” Paradigm. Technical report. Institute for New Economic Thinking.

G. Dosi, G. Fagiolo, M. Napoletano, A. Roventini, T. Treibich (2014), “Fiscal and Monetary Policies in Complex Evolving Economies”. Available at SSRN eLibrary:

Dosi, G., Fagiolo, G., Napoletano, M. Roventini, A., 2013. Income Distribution, Credit and Fiscal Policies in an Agent-Based Keynesian Model. Journal of Economic Dynamics & Control. .

Dosi, G., Fagiolo, G. Roventini, A., 2010. Schumpeter Meeting Keynes: A Policy-Friendly Model of Endogenous Growth and Business Cycles. Journal of Economic Dynamics & Control. 34, 1748–1767.

Krugman, P., 2011. The Profession and the Crisis. Eastern Economic Journal. 37, 307–312.

Kumhof, M. Rancière, R., 2011. Inequality, leverage and crises. VoxEU. 4 February.

Lucas, R. E. J., 2009. In Defence of the Dismal Science. The Economist. August, 6th, .

Stiglitz, J., 2011. Rethinking Macroeconomics: What Failed, and How to Repair It. Journal of the European Economic Association. 9, 591–645.

Stiglitz, J., 2012. The Price of Inequality: How Today’s Divided Society Endangers Our Future. WW Norton & Company.

Tesfatsion, L., 2006. ACE: A Constructive Approach to Economic Theory. In Handbook of Computational Economics II: Agent-Based Computational Economics, L. Tesfatsion K. Judd (eds). Amsterdam, North Holland.

Trichet, J., 2010. Reflections on the nature of monetary policy non-standard measures and finance theory. In opening address at the 6th ECB Central Banking Conference, Frankfurt am Main. Vol. 18.

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nkostava's picture

GSS needs scientific tools

I would like to add a brief comment to this discussion on. It is clear that GSS is a widely multidisciplinary approach, and a variety of problems can be addressed using a GSS approach. Therefore GSS is not an application domain, but more akin to a scientific approach to looking at the world.

Therefore, I believe that it is important for GSS research to develop fundamental research *tools* that will accelerate future research in this area. It seems to me that a lot of the discussion has focused on applications of GSS, but I believe that we should consider how to grow GSS as a scientific discipline of its own right, and for that we need to develop GSS tools (software, theories, etc) that can help scientists conduct GSS research.

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nweisbge's picture

Science for Policy : some issues

GSS presently focuses on developing new tools to facilitate the uptake of science and technology results by policy makers. But what we, scientists, often miss is a clear understanding of political decision processes, institutions, political actors at all levels. The gap between scientists and policy makers is bi-directional; for many reasons, policy makers might lack competence, time, interest in our conclusions, but on the other hand our message would have more impact if we knew whom we are addressing, what are the set of issues that our interlocutors are facing, what are their constraints,
what is their real influence and so on.

Environmental issues provide many examples of the complexity in decision making. At a higher level, often also taken by scientists, regulation to be imposed to practitioners is considered as the solution. To take the example of food supply and the Common Agricultural Policy, the general directives can be discussed in Brussels, but the big issues are in fact local implementation. Most food is produced by farmers and fishermen, often individuals, and decisions not only involve farmers but a lot of intermediary institutions such as agricultural counselors, farmers union, local authorities, not too mention consumers and the numerous related market institutions. Furthermore on issues such as the use of pesticides and GMOs, we adopt a rich westerner vision, neglecting the urgency of the needs of poorer nations. More generally, many of the Global Systems under study display a decision and institution structure as complex as the natural subsystem on which scientists may have developed good models. Decisions concerning Health systems depends upon institutions such as hospitals but also upon individual doctors, insurance companies, local cultural practices. Pollutions and the associated health risks depends on the practices of industries which can abide to regulations, or find many escapes to avoid them.

My bottom line should become clear by now: to improve our understanding of political decision processes, institutions, and political actors, we might want to include social and political scientists in GSS consortia. And once again this raises many issues: our cultures are different, their modeling experience is often standard macro-economics, larger consortia are more difficult to build and to manage. But some foreign experiences, American Think Tanks such as the Brookings Institution, or European success stories such as FOCs collaboration on Financial crises, and the large set of results obtained in the Sociology of agriculture testify that the task is not impossible.

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nmedomma's picture

Brief feedback

I will try to reflect on the questions posted in the text that introduces this topic. First of all, I feel that its orientation is too broad. Of course, global systems cover all different aspects of our lives, but to cover all of them at once in one initiative looks over-ambitious and has the potential to hamper potential progress. Several different communities have emerged, including a newly forming broad GSS community, which address systemic risk, complex networks, econophysics, and other areas. Mapping of the existing communities could help to decide which of the problems should received the biggest attention within GSS.
I would suggest the development of practically applicable GSS tools as a potential goal. The idea is that majority of complex systems science is now custom made to tailor a specific system and conditions. What we lack are universal tools that would produce useful output without the necessity to invest months or years of research effort to answer a particular task. Real-time monitoring and predicting centers, if you want. The reputation of GSS would be hugely enhanced by showing that there are such potential practical outcomes. The other, related, question is the question of limits of predictability in complex systems. In weather predictions, we have a good knowledge of the current conditions and know precisely the underlying equations, yet reliable predictions are not possible for horizons longer than a few days. In complex systems, we do not even fully know the underlying equations... Are there complex systems where no reliable predictions will ever be possible? Or, rather, which questions we can and which we cannot ask in complex systems?

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nhaasarm's picture

GSS - Inter- and Transdisciplinarity at Work

Dear all,
GSS is a concept, a toolbox, and a community that is very well positioned to accomplish interdisciplinary and transdisciplinary research. With my own research, I want to give an example for this statement.

Benefitting from interdisciplinary work

The British economist John Kay mobilized insights from nuclear power engineering for thinking about the financial system. The basic insight of nuclear engineers was that the design of nuclear power plants should be such that the single components of a nuclear power plant should not be too densely coupled. Otherwise, a potential failure of one component could propagate, impact on the connected components, and risk their functionality.
Applying the same design principles to financial markets, Kay came to the conclusion that in order to make the financial system more resilient towards shocks, shorter and simpler linear chains of intermediation would be needed. Moreover, financial players should only loosely be coupled in order to enhance the loss absorption capacity and resolution capability of the financial system as a whole. This is in striking contrast to the fact that in recent decades, the financial system moved towards ever-closer integration.
Remarkably, the famous British economist John Maynard Keynes held similar views. He thought hard about an international financial system that would facilitate world trade and international capital flows, but at the same time leave sufficient room for manoeuvre for national governments to address specific domestic needs. In particular, he was adamant that countries must have sufficient discretion for their domestic fiscal, wage and monetary policies.
In Keynes’ time, he did not have the appropriate tools available for sustaining his conviction by big data or complex computer models. Nowadays, we have them. A paradigmatic example is the research looking into the topology of the financial network as conducted by the EU funded research projects SIMPOL and FOC, and the too-connected-to-fail insights that Stefano Battiston discussed in his feedback given above.

Transdisciplinarity at work

The recent conference Stefano mentioned in his contribution above ( is a brilliant example for transdisciplinary research as it engaged actual central bankers into discussions with GSS scientists who are pioneering interdisciplinary research. These discussions concern theoretically very complex scientific issues that are adamant for the stability of the financial system.
Another example for transdisciplinarity at work is a workshop series devoted to the quest for a sustainable financial system ( This workshop series is a joint venture of the Institute for Advanced Sustainability Studies, Potsdam, Germany, and the Global Climate Forum. Its rationale is to bring together stakeholders from the sustainability community and the community interested in the world financial system in order to discuss the systemic issues raised by Kay and Keynes. Key is to involve stakeholders with very different backgrounds from policy, financial business, the real economic sectors, and civil society.
For communicating complex systemic features of the financial system to non-experts, we need new communication tools. GSS has, for example, the potential to develop innovative graphical interfaces for communicating the complexity of the financial system to non-experts. Moreover, GSS can and should engage with communication experts from the new media and with artists to reach out to civil society.

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nkiddkpu's picture

Art in GSS should not be about communication

While some artists may be interested in undertaking this task of communicating - the art as communication paradigm - many will not be interested, and this is not what art deployed in GSS should be about. Art is a means of undertaking research, thinking in terms of systems, transcending, and looking at the world in a different way - the opening peoples' eyes and changing consciousness paradigm. GSS needs such a perspective, otherwise it remains caught up in the past - mechanistic, reductionist, delusional - and the past has self-evidently failed, otherwise there would be no interest in GSS! It is time for a paradigm shift and such will not be achieved by thinking that art is to be deployed as a meaning of communication. The future is art, only, as always, when faced with revolutions in thought, those who think in the old paradigm hold on to it regardless!

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nvrochst's picture

Global monitoring

In my view global (or world) information monitoring could provide important information to support decision making and risk assessment. World monitoring includes several challenges and problems such as news and media monitoring (including social media), environmental monitoring, crowd behaviour, epidemics etc. Although the aforementioned problems lay in different areas (e.g. media, environment, security, health etc.), there are specific ICT challenges identified and technologies that could contribute. Specifically all these problems require semantic integration of heterogeneous and distributed large-scale data. The multimodality of the content calls for the need of techniques to extract semantic information from multimedia (audiovisual) resources. It is also very important to apply techniques for validation and reputation of the "sensors" that provide these data since some of them might be considered unreliable due to several reasons (e.g. a station very far from the area of interest, a rumor blog etc.). Emphasis should be given to topic detection based on stream data (including multimedia and social media), alerts and detection of complementary and contradictory data. Fusion of such data (depending on the problem) is also very challenging. Finally, the end user side requires a holistic view of the results. This calls for the development not only of visualisation techniques but also for reasoning and statistical recommendation for decision support. Summarisation of information is also of importance.

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nkiddkpu's picture

Global monitoring = abuse

The Americans are already doing what is proposed and we should not be giving them (and other Nation States) even more powerful tools to monitor the world - us. Think civil liberties, think time for a change, think rejection of this monitoring, control, and power paradigm, just think ... This is why artists are important … This is why we need artists as researchers in FET and GSS.

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nmarcojs's picture

Suggestion for an open platform to address GSS challenges

Hi, my (naive) view is that many of the objectives are already being addressed by the companies who have not only access to the data and resources for processing it, but also software tools. Two examples are Google and Microsoft, and the results of their research start to appear in many cross-disciplinary research forums (like RDA, the Research Data Allianz, or AGU, covering most teledetection systems)
In my opinion the record of the human and non human activities available now is enough to advance in many GSS areas.
However a common open platform integrating:
-data sources
-processing resources
-simulation models (like multi-million agents systems) with adequate multi-level support
-analytic tools
could be applied now to many fields in GSS and get new realistic results.
The "good" point is that many of that components are already there. The "bad" side is that large companies with a clear business focus and enough resources and expertise are doing it, and they may exhaust the field.
Linked to the platform the need for a common training, or even better "formation", not only for researchers but also for high level technicians with multi domain expertise is needed.
So my suggestion is to make an effort at EU level in a core team, not so many resources are needed, to identify the existing options for the components and propose an integration in an open platform. Then, setup a call to exploit the platform in different lines. I know it is not very original, but it could work.

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nsanmimi's picture

GSS and urbanism/cities

GSS and urbanism/cities
As for the first question on this consultation, I believe it is good to identify some general topics within GSS, but also to leave the door open to new ideas and initiatives. Within the already identified research direction on urbanism and cities, a useful background document is the report on GSS and urban development summarizing the contributions to the Oct. 2013 workshop organized by the EUNOIA consortium ( A multi and transdisciplinary research community is emerging in this area of research as identified for example in the satellites meetings of ECCS2013 ( and ECCS2014 ( What is needed to consolidate this emerging community is the development of research projects with specific goals and the participation of complementary teams. These networks would create the appropriate community network. Also an open platform to share data on urban studies would be instrumental for significant advances in the field and the participation of different stakeholders
I see important research challenges at three different levels:
i) In the Big Data era, theory is necessary: We need to develop GSS unifying concepts that provide qualitative and quantitative understanding of urbanism and cities
ii) In cities there are infrastructure, environment and social ingredients. It is the social dimension the one that today offers the most important research challenge and opportunity.
iii) Global system of cities: The challenge is to quantify and characterize the the network of interactions among cities, including flows of people, information and trade.

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nmaksyur's picture

Artificial intellect

Artificial intellect of the Society
Keywords: social intellect, network, emergent knowledge.
Topics to be addressed are interdisciplinary.

Artificial intellect is usually conceived of as a sophisticated supercomputer dealing with digital objects. But real thinking essentially involves such non-digital components as premonition, vague measuring, paradox association, prejudice and other. So artificial thinking must include feelings of people and be implemented as a man-machine system. Such a system may be built up as a specifically structured social net.

The Net may be composed of the following subnets which for convenience are given names.

1. Linguist
He deciphers the message of the user of the Net and addresses it to the knowledge base. If the knowledge base (a collection of multimedia files) has the needed information the user receives it. If not he sends the message to the subnet Usher.
2. Usher
He decides which address of the knowledge base must be completed and sends the order to the subnet Butler.
3. Butler
He must fill in the empty address received from the Usher and for this purpose starts collecting the necessary scientific data by sending a request to the subnet Surfer. After receiving the data he fills up the knowledge base with files containing the scientific reply to the collected data.
4. Surfer
He surfs the WWW, validates the data on the maximum quantity of information and sends the data to the Butler. The Surfer may have the data synthesized.
5. Keeper
He monitors the overall working of the Net and undertakes the necessary corrections in case of possible failours.

At the first glance the Net functions as an expert system but all the experts are unaware of the user’s demand and the response of the Net comes out to be an emergent knowledge thus produced by an artificial gadget.

Guiding features:
• This topic addresses the coupling between science and social conscience.
• The state of the art is poor. Frontier research calls for fundamental shifts in economics.
• The topic is deeply interdisciplinary involving all the possible ways of data mining.
• The research can be carried out by few European scientists if the knowledge base should be constrained only to energy policy scenarios. Currently the energy policy is very uncertain.
• This topic became reasonable due to the expansion of WWW.
• This research is needed to make the economy more stable.

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ncnojuan's picture

Tool to combine bottom-up and top-down approaches to organising

In recent understanding of organisations, the view has shifted from considering them as the product of managers creating and enforcing policies, procedures and rules, to a view where organisations are the product of everyday interactions carried out by each and every member. The role of informal networks and structures within organisations has not only been acknowledged but also emphasised, becoming a rising trend in organisational research.

Adopting a pure top-down approach to organising may stiffen innovation and introduce inefficiencies, as well as problems with more human factors as satisfaction and engagement. But the opposite, self-organised approach increases the difficulty to predict and control the organisation, as well as creating difficulties in decision making and diffusion of knowledge and ideas.

As organisations are not static, defined once and immutable in time, but constantly being redefining itself according to its environment and it’s internal situation, striking a balance between both approaches, bottom-up and top-down, is key to the survival of the organisation.

A tool capable of informing members of an organisation of possible paths of action, based on an understanding of the external and internal conditions at any moment, and even capable of making decisions and taking action on its own would be of high value for everyone involved in an organisation. The tool would take into account communication processes, structural factors, members' social networks, task processes and requirements, and external forces influencing the organisation in order to provide solutions to different scenarios.

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nherrric's picture

GSS and policy applications

GSS is a relevant and necessary topic in the context of European research. The intrinsically holistic and eclectic approach advocated by GSS fills a gap that is not addressed by the policy-oriented topics of the EC mainstream programmes (Transport, Energy, Environment, etc.), which are typically focused on incremental, piecemeal measures and leave little room for transdisciplinary approaches.

In terms of the orientation of research, broadly speaking, I think GSS should be based on two main pillars:
- An integrative approach to data analysis and theoretical modelling: with the emergence of big data there is a risk of focusing on descriptive work and on predictive, non-explanatory models, abandoning theory. In a first stage, big data may be an opportunity to calibrate and validate existing models with richer data, but in the future it may also lead to new modelling approaches that make the best use of new, emerging data sources.
- Policy interfaces. Ultimately, the benefits of GSS will only be realised if the newly developed models and tools are integrated into decision making processes. The development of the models needs to be accompanied by an effort to understand such processes and a continuous dialogue between scientists and decision makers.

A detailed discussion of these questions for the particular case of urban planning can be found in the position papers of the GSS projects EUNOIA ( and INSIGHT (, as well as in the report on GSS and Urban Development prepared by the EUNOIA consortium and already mentioned by Maxi in a previous comment (the three documents can be downloaded from:!publications/caud).

The construction of transdisciplinary research teams able to integrate knowledge on data analysis and complex systems with domain-specific knowledge and real-world experience in policy making processes is a key condition for GSS projects to deliver actual benefits for policy decision making. On a more personal note, I think a good example of this is the EUNOIA project, which has delivered a number of interesting scientific results, but has also managed to transfer some of these results into products and services for urban planners and transport practitioners that we in Nommon ( are now bringing to the market. In my opinion, although the focus of FET is mainly on medium- to long-term research, some of the research elements included in GSS are now mature enough to deliver practical applications. At the same time success stories like this would not have been possible without the sort of transdisciplinary collaborations enabled by GSS.

Finally, regarding the practical implementation of hypothetical future GSS calls, I think projects should remain open in terms of the domain of application so as to leave room for new ideas and initiatives, with the only condition of justifying their potential to contribute to addressing relevant policy questions. The composition of the research teams should reconcile the ability to produce new knowledge with the delivery of innovative ‘quick wins’ in the nearer term, as well as to link with other related initiatives at international level (an example in the area of human development is the UN Global Pulse initiative,

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ncincosi's picture

GSS and Agent-based Macroeconomics

Dear All
In our globalized world, policy-makers face complex decision. They must deal with a system of markets in a world of States. Many markets are still mostly regionally organized, but the number of globalized markets has risen tremendously in the recent past. Foremost, financial markets have increasingly interconnected all parts of the globe. Society and economy have become more unstable and unpredictable than ever. The economic and financial crisis and the quest for an economical and environmental sustainable development constitute fundamental issues for citizens and policy makers.
The governance of local and global economic systems is therefore a topic of paramount importance, and developing adequate innovative tools to support decision-makers is a pressing issue. In order to successfully understand and govern this change, it is crucial to focus our attention on the increasingly integrated market economy and finance, which essentially drive other important global issues like the climate change and other environmental questions, food security, or energy management. In this light, we need to enrich our current knowledge of the economic mechanisms and to develop new tools for policy.

The standard type of model currently used in macroeconomics is the Dynamic Stochastic General Equilibrium (DSGE) modelling approach. DSGE models have some distinguishing features. Firstly, they are micro-founded models, i.e. the behavioral equations describing the economy are derived from a utility maximization problem at the micro level. Secondly, DSGE models assume that agents have rational expectations, i.e., agents use the using all the available information (including their knowledge of the economic models and mechanisms) to compute the expected values of relevant economic variables. In this way, rational agents make mistakes in their predictions in the short run but they do not make any systematic errors in the long run. Despite their popularity, these models have been widely criticized (see e.g., Caballero (2010), De Grauwe and Honkapohja (2009))).

The pre-crisis research agenda of macroeconomics was to improve the consensus among macroeconomists and further to refine the DSGE model. However, the crisis has drastically modified this agenda and has led to an intense debate about the modelling tools currently available. Indeed, the recent crisis has pointed out the necessity to move from the concepts of free-market and efficiency to regulation and resilience. Following the crisis, there have been many conjectures for the possible origin of instability, e.g., collective behavior, lack of trust and psychological components in agents’ behavior, contagion and network domino effects, liquidity crises, and leverage effects, etc..

Agent-based models can help to understand the economic crises, given that they can easily address liquidity problems, bankruptcies, domino effects, systemic risk, speculative bubbles, and credit crunches (see e.g. Cincotti et al. 2010).

Given the above-context, agent-based models started to deal with macroeconomic modelling. In this respect, one of the first and prominent attempts has been performed within the EU-FP6 FET Proactive project Eurace ( The three-year project Eurace (started 2006 under my coordination) developed an agent-based artificial economy and showed a rich scenario of interactions between real and financial variables. Eurace is a large-scale agent-based model and simulator representing a fully integrated macroeconomy consisting of three economic spheres: the real sphere (consumption goods, investment goods, and labor markets), the financial sphere (credit and financial markets), and the public sector (Government and Central Bank) - see Cincotti et al. (2012a). Following the agent-based approach, Eurace economic agents are characterized by bounded rationality and adaptive behavior as well as pairwise interactions in decentralized markets. The balance-sheet approach and the stock flow consistency have been followed as a key modelling paradigm in Eurace. The computational results show the real effects on the artificial economy of the dynamics of monetary aggregates, i.e. endogenous credit money supplied by commercial banks as loans to firms, and fiat money created by the central bank by means of quantitative easing (Cincotti et al., 2010, and Raberto et al., 2012). In particular, Eurace shows the emergence of endogenous business cycles which are mainly due to the interplay between real economic activity and its financing through the credit market, thus shedding light on the relation between debt, leverage and main economic indicators (Raberto et al., 2012, Teglio et al. 2012). Moreover, Eurace shows that a quantitative easing monetary policy coupled with a loose fiscal policy generally provides better macroeconomic performance in terms of real variables, despite higher wage and inflation rates (see Cincotti et al., 2010). The Eurace model has been also employed to test regulatory policies providing time varying capital requirements for banks, based on mechanisms that enforce banks to build up or release capital buffers, according to the overall conditions of the economy, in line with the new Basel III regulatory framework. Results (Cincotti et al. 2012b) have shown that the dynamic regulation of capital requirements is generally more successful than fixed tight capital requirements in stabilizing the economy and improving the macroeconomic performance.

More recently, the Eurace agent-based macroeconomy has become the base for the AB engine of the EU-FP7 CNET ICT GSS project Symphony ( The three-years project Symphony (started 2013 under my coordination) is orchestrating a set of tools that will be able: (i) to collect and analyze relevant information by means of social media mining tools and web-based information markets; (ii) to simulate the complex economic dynamics by means of an agent-based model of the global economy, explicitly designed for policy making; (iii) to involve citizens in the decision making process through a serious game interface, and through a set of information markets on the artificial economy that will allow us to overcome the huge economic impasse of properly modeling expectations.

Consequently, the Eurace agent-based macroeconomy has been redesigned and is currently under development so to include real estate market, raw material and energy markets, derivatives, foreign sector, waste and pollution. The final goal is to better represent the global techno-socio-economy and (coupled with innovative human machine interfaces and ICT tools) to provide policy-makers with an innovative instrument for the design and testing of economic policies and regulatory frameworks, to improve awareness of citizens, to increase transparent and therefore re-establishing trust in public policy institutions, to endogenize economic variables considered externalities by neoclassical models, to enhance sustainability and resilience of the economy so to support the prevention and mitigation of economic and financial crises and the fostering of an economically and ecologically sustainable growth path in a shareholder driven agenda. It is worth remarking that the focus on resilience and sustainability is coherent with the change from efficiency to regulation in the perspective of macroeconomics and with the EU historical approach to society.

Eurace and Symphony, together with other similar successful stories granted either at European research programme on by European state member schemes point out some major outcomes:
1. Agent-based macroeconomics is mature to address key question in the real economy in a shareholder driven research activity;
2. Agent-based macroeconomics is an European assets;
3. Irrespective to the controversy that agent-based macroeconomics is facing by large fraction of the US economist community, the rest of the international community is emulating the European path (e.g., a Chinese research team is specializing an Eurace offspring to their domestic context).

It is worth noting that the reaction of the US economist community (with however limited in number but of great relevance cases of consensus) is not surprising as the neoclassical economic theory has been formulated in the US and is there considered US human capital. What is not yet completely understand is that agent-based macroeconomics covers that same role but for the EU and thus that is not only a European assets but also a European human capital.

Therefore, the EU has both the opportunity and the responsibility to foster and to consolidate the research agenda on agent-based macroeconomics. To this aim, Global Systems Science represents the natural context as the globalized economy and its markets are the archetypal example of a complex global system.

In this direction, several options are available and I would like to provide a personal tentative to-do-list:
a. To continue supporting small size projects on agent-based macroeconomics in stakeholder driven research activities
b. To define a medium/large size coordination program among the groups and the related successful stories so to assess the EU position in the context of agent-based macroeconomics
c. To promote an EU leaded global research agenda in agent-based macroeconomics

As regarding point a., the great advantage offered by small size projects relay mostly in the costs-benefits relationship. In general, at the risk of a limited budget a stakeholder driven research project can result in large outcomes in a new contest not yet addressed by other initiatives.

As regarding point b., it represents the other side of the same coin with respect to point a. In fact, when a contest is consolidated and several alternatives are available, a medium/large size coordination program results mandatory in order to assess the know-how, to orchestrate the best practices and to define the arena for comparison and cooperation among the alternatives.

As regarding point c., attention should be dedicated to the international community starting from those with the most open. This might result in a limited cooperation with the US in the short run, but it will contribute to assert an alternative at international level to the human capital in economics that might result effective in the long run. In this respect, an initial opportunity can be found in the Chinese National Science Foundation that is currently considering a research line similar to GSS in economics for a 10 years research programme. Unfortunately, the pilot call has been reserved only to scholars with Chinese nationality, but a cooperation between EU and China might help in overcoming such limitations.

Caballero, R.K. (1992), A fallacy of composition, American Economic Review, 82(5): 1279-1292.
Cincotti S., Raberto M., Teglio A. (2010). Credit money and macroeconomic instability in the agent-based model and simulator Eurace, Economics: The Open-Access, Open-Assessment E-Journal, 4, 2010-26.
Cincotti S., Raberto M., Teglio A. (2012a). The EURACE macroeconomic model and simulator. In: M. Aoki, K. Binmore, S. Deakin, H. Gintis. Complexity and Institutions: Markets, Norms and Corporations. p. 81-106, Palgrave Macmillan
Cincotti, S., Raberto, M., and Teglio A., (2012b). Macroprudential Policies in an Agent-Based Artificial Economy, Revue de l’OFCE, Debates and policies, 124: 205:234.
De Grauwe, P. and Honkapohja, S., (2009). The macroeconomy, in vital questions, The contribution of European social science, European Science Foundation.
Greenwald, B.C and Stiglitz, J. E, (1993). Financial market imperfections and business cycles, Quarterly Journal of Economics, 108(1): 77-114.
Raberto, M., Teglio, A., Cincotti, S. (2012). Debt deleveraging and business cycles. an agent-based perspective, Economics: The Open-Access, Open-Assessment E-Journal, 6, 2012-27.
Teglio A., Raberto M. and Cincotti, S. (2012). The impact of banks’ capital adequacy regulation on the economic system: an agent-based approach. Advances in Complex Systems. Vol. 15, issue supp2.

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nkiddkpu's picture

Global Systems Science - The Sum of Things

Most people are familiar with the image of a kettle being heated over an open fire. The kettle in this image is a proven classic design whose origin is lost in time. The form of this kettle is the way it is, because of the requirement to be able to suspend the kettle over a fire, which, in the distant past, was how people cooked. The handle enables the metal body of the kettle to be suspended from a hook over the fire, and the spout of course provides the route by which the boiled water can be poured into another receptacle. Surprisingly though, this design survived the transition from the open fire to the cooking stove with its hot plates, and then, in the early 20th century, the transition to the electric kettle. By this stage though, the design was no longer relevant, because the source of the heat had been built into the kettle. Yet externally nothing changed. It was only in the 1980s that someone understood that this iconic design was no longer necessary, and then had the courage to propose a new design – thus the modern tower kettle was born.

A similar thing happened in the early days of the film industry. Early movies were just, in effect, filmed versions of stage plays, that followed a linear chronological sequence of events, which represented the norm at the time. Yet in this case, very quickly people released that the camera liberated the script from the constraints of time and place, and that no longer was it necessary to follow a linear flow of events, and that also the camera enabled illusions that were not otherwise possible. And so it goes with literature too. For centuries people wrote novels as a linear chronological order of events, until someone, just after the Great War, wrote a novel that jumped about in a time sense, moving backward and forward, from present time to past time, and thus modernism arrived in literature.

The message of the above is clear – we are indeed creatures of habit. And what goes for kettles, films and novels, is also a summary of a large number of the inputs to the consultation on Global Systems Science – many just accept the kettle as it is and propose adjustments and refinements. A few people however have proposed radically new designs. These new designs consider: the use of art as part of the methodology; inclusion of what is called citizen science; adding behavioural (social science) aspects to the recipe; introducing time as a central element of GSS; generalising GSS towards a new way of undertaking scientific research; integrating Responsible Research and Innovation as an integrated aspect of method; moving beyond interdisciplinary thinking to encompass transdisciplinary operation in the sense of transcending the traditional organisation of knowledge; and shifting the focus away from policy towards the design of new systems.

So what is FET about? Will we stick with the kettle design as it is, or reinvent it completely? Which best captures the spirit of FET? Which is higher risk? Which is more visionary? Which is more likely to lead to transformational impacts and the much talked about disruptive effects? At this challenging point in Europe’s long history, what does Europe most need – an old design that is no longer necessary or a new one that can contribute to the making of a different future?

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nkarcani's picture

Systems Complexity: Evolving Systems and Systems of Systems

“Systems Complexity: Evolving Systems and Systems of Systems”

Nicos Karcanias
Systems and Control Research Centre,
School of Mathematics, Computer Science and Engineering
City University London, Northampton Square, London EC1V 0HB, UK

Aim of this Input
The area of Global Systems is fundamental for developments in the field of Complex Engineering and the field of Cyber-Physical Systems. The following contribution discusses the need for a Proactive Call in Global Systems that looks at the system challenges in the wider engineering field.

Complexity in Engineering
Complex Systems is a term that emerges in many disciplines and domains and has many interpretations, implications and problems associated with it. The specific domain provides dominant features and characterise the nature of problems to be considered. A major classification of such systems are to those linked with physical processes (physics, biology, genetics, ecosystems, social etc) and those which are man made (engineering, technology, energy, transport, software, management and finance etc) and deal with the “macro level” issues and technology. Each of the above classes has its own key paradigms, specific problems, concepts and methodologies. There exist however generic common issues amongst the different domains and this requires the need for developing generic methodologies and tools that can be applied across the different domains. For man made systems, Systems and Control concepts and tools are important in the development of methodologies aiming for the Management of Complexity.

Existing methods in Systems and Control deal predominantly with fixed systems, where components, interconnection topology, measurement-actuation schemes and control structures are specified. Two new major paradigms expressing forms of engineering complexity which have recently emerged and they are the new paradigms of:

? Structure Evolving Systems (SES)
? Systems of Systems (SoS)

Using the traditional view of the meaning of the system (components, interconnection topology, environment), the common element between those two new paradigms is that the interconnection topology may vary, evolve in the case of SES, whereas in the case of SoS the interconnection rule is generalised to a new notion of a “play” .

Structure Evolving Systems : Such a class of systems emerge in natural processes such as Biology, Genetics, Crystallography etc; the area of man made processes includes Engineering Design, Power Systems under de-regulation, Integrated Design and Re-design of Engineering Systems (Process Systems, Flexible Space Structures etc), Systems Instrumentation, Design over the Life-Cycle of processes, Control of Communication Networks, Supply Chain Management, Business Process Re-engineering, Data Processes etc. This family departs considerably from the traditional assumption that the system is fixed and its dominant features relate to:

¦The topology of interconnections is not fixed but may vary through the life-cycle of the system (Variability of Interconnection Topology Complexity).
¦The overall system may evolve through the early-late stages of the design process (Design Time Evolution).
¦ There may be Variability and/or uncertainty on the system’s environment during the lifecycle requiring flexibility in organisation and operability (Lifecycle Complexity).
¦ The system may be large scale, multi-component and this may impact on methodologies and computations (Large Scale – Multi-component Complexity).
¦ There may be variability in the Organisational Structures of the information and decision making (control) in response to changes in goals and operational requirements (Organisational Complexity Variability).

The above features characterise a new paradigm in systems theory and introduce major challenges for Control Theory and Design and Systems Engineering. There are different forms of structure evolution. Integrated System Design has been an area that has motivated some of the early studies on SES (early work in Process Control EU Project EPIC , EU FET project SESDIP ). The integration of traditional design stages, such as Process Synthesis (PS), Global Instrumentation (GS) and finally Control Design (CD) is an evolutionary process as far model system formation and two typical forms of evolution are the structural design evolution, the early-late design evolution and the interconnection topology evolution . Methodologies and tools developed for Fixed Structure Systems (FES) cannot meet the challenges of the SES class and new developments on the level of concepts, modelling, analysis and synthesis methodologies are needed. Although the conceptual developments can be generic, the relevant methodologies and tools are specific domain (model nature) dependent and this requires focusing on specific problem areas. The research is strongly influenced by the need to address life-cycle and re-design issues and such problems have a strong technological and economic dimension. The main challenges for this research come from:

• Lack of knowledge, or difficulties in characterizing the behavior of the basic process, or sub-processes (Unit Behavioral Complexity).
• Complexity of computational engine associated with a sub-processes (Computational Complexity).
• Difficulties in characterizing the interconnection topology of sub-processes and/or variability, uncertainty of this topology during the system life-cycle (Interconnection Topology Complexity).
• Large scale dimensionality and possibly multi-component character that impacts on methodologies and computations (Large Scale – Multicomponent Complexity)
• Heterogeneous nature of sub-processes, which in a given interconnection topology, results in hybrid forms of overall behaviour (Hybrid Behavioural Complexity).
• Organisational alternatives for the functioning, information and decision making (control) structures in respond to goals and operational requirements (Organisational Complexity).
• Variability and/or uncertainty on the system’s environment during the lifecycle (changing goals, requirements, disturbances, structural changes) which require flexibility in organisation and operability (Lifecycle Complexity).

Such issues are crucial for the development of solutions for this new engineering paradigm characterised by types of complexity linked to structural variability, behavioural variability and possibly large dimensionality. The overall objective of this research is to develop methodology and tools for the class of Structure Evolving Systems which aim to:

. ? Develop tools for representation and modelling of forms of system evolution.
? Address issues of “system organisation” and develop relevant modelling tools.
?Quantify the nature of emergent properties.
?Manage complexity in design
?Develop Systems Engineering tools to address design and re-design in an integrated way.

System of Systems: The notion of “System of Systems” (SoS) has emerged in many fields of applications from air traffic control to constellations of satellites, integrated operations of industrial systems in an extended enterprise to future combat systems. Such systems introduce a new systems paradigm with main characteristic the interaction of many independent, autonomous systems, frequently of large dimensions, which are brought together in order to satisfy a global goal and under certain rules of engagement. These complex multi-systems are very interdependent, but exhibit features well beyond the standard notion of system composition. They represent a synthesis of systems which themselves have a degree of autonomy, but this composition is subject to a central task and related rules frequently defined as “system plays” expressing the subjection of subsystems to a central task. This generalisation of the interconnection topology notion introduces special features and challenging problems, which are different than those presented by the design of traditional systems of the engineering domain. The distinguishing feature of this new form of complexity is :

• The role of “objects”, or “subsystems” of the traditional system definition is taken by the notion of the autonomous agent, which may be characterised by some form of intelligence.
• The notion of “interconnection topology” of traditional systems is generalised to that of “systems play”.
• Decision making and control may take the form of a game amongst the subsystems.

In this set up emergence takes a new form. There is a number of fundamental challenges, if the issue of design, or re-design SoS is to be addressed and the shaping of a new form of System of Systems Engineering methodology is to be addressed. The central challenges are:

? Develop a framework, concepts and tools for the representation of the system plays in SoS.
? Define the fundamental system properties in the context of SoS.
? Quantify the nature of emergent properties in the context of SoS.
? Develop game based formulations for Decision and Control problems in SoS.
? Develop tools for the Management of Complexity in design, re-design of SoS.

The above are crucial building blocks in the effort to develop Systems Engineering tools which may address design within the SoS context in an integrated way.

Addressing the issues of SES and SoS has important implications for the underpinning Control Theory and related Design methodologies. Control Theory and Design has developed considerably in the last forty years. However, the underlying assumption has always been that the system has been already designed and thus control has been viewed as the final stage of the design process on a system that has been formed. New paradigms have emerged which enlarge the area where Control is relevant and which challenge the ”fixed system structure assumption”. These force us to reconsider some of the fundamentals (viewing Control as the final design stage on a formed system) and create the need for new developments where Control provides the concept and tools intervening in the overall design process, even at stages where the system is not fixed but may vary, may be under some evolution. Traditional Control has been capable to deal with uncertainty at the unit process level, but now has to develop to a new stage where it has to handle issues of structural, dynamic evolution of the system as well as control in the context of a “systems play”.

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nedmonbr's picture

Understading complex socio-ecological interactions

Both ecological and social systems are complex, but the interaction between them even more. Many previous societies have killed themselves off and, in the process, devastated their environments. Perhaps the most famous of these is that of “Easter Island”. This suggests a grand challenge: that of helping discover what kinds of rationality and/or coordination mechanisms might allow humans and the greatest possible variety of other species to coexist. As their contribution towards this, the GSS community could investigate these questions within simulations to suggest hypotheses as to how this could be done. The particular problem for our community is that of designing and releasing a society of plausible agents into a simulated ecology and assessing: (a) whether the agents survive and (b) if they do survive, what impact they have upon the diversity of other species in the simulation. No other community is currently in a position to explore this problem as a whole. The simulated ecology needs to implement a suitably dynamic, complex and reactive environment for the test to be meaningful. In such a simulation, agents (as any other entity) would have to eat other entities to survive, but if they destroy the species they depend upon they are likely to die off themselves. Up to now there has been a lack of simulations that combine a complex model of the ecology with a multi-agent model of society – there have been complex models of society but with simple ecological representations and complex ecological models but with little of human social complexity in them. In order for progress to be made with humanity’s challenge, we will have to move beyond simple ideas and solutions and embrace the complexity of the socio-ecological complex as a whole. A suitable dynamic ecological model would be the first step towards a meaningful test bed to under pin the implied research programme.

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nborkowo's picture

Socio-ecological models

I agree very much. As a biologist by education, and by practice creator of simulation programs, I'm very interested in similarities and interactions between biological and social phenomena. And their emergent properties, not easy to catch using classical tools, both reductionistic, as in science, as well as holistic from humanities.
You know the concept of memetics. It was considered to be very promising for a while, but in practice did not go beyond the theoretical digressions. In my opinion because of the lack of appropriate tools at the time.
But now, using such tool like computer simulations and big data, especially about social networks
we have a real opportunity to push things forward.

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ndepelfo's picture

New Design and Engineering of Socio-Technical Systems

I think that a research area where potentially new strong results are possible and currently missing is the connection of GSS to the design of Socio-Technical systems. In particular, when societal actors are part of a system to be designed, e.g, when the aim is to derive a certain set of policies, current engineering methods fall short in coping with the features of emerging Socio-Technical systems, i.e., complexity and often only partial knowledge of the specific interactions taking place at the micro scale. Still, we clearly want to be able to quantify the performance of our design and to provide confidence level in the investments that we perform.

In designing a system, a traditional engineering procedure, in fact, would start straight on requirements, look at current practices and rules of thumb, and would try to enforce those requirements by controlling system components and by ruling local interactions. But, those engineering tools are currently missing: this especially true if we aim at designing a socio-technical system where strategic interactions take place at the components' level. In such cases, in fact, agents in the system may well react to the design by adopting specific behaviors according to their own utilities which hence should be factored in at design time.

My understanding of the state of art is that this requires still a fundamental merge in Economics, Engineering and Complex System science to come up with such a novel, groundbreaking set of system design results and methodologies.

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nnowakaz's picture

Global Sytems Initiative: capitalize on opportunities

Comment on Global Systems Initiative
In my opinion Global Systems Initiative should have the highest priority for being continued. Today humanity faces a global crisis in many areas including environment, energy, finances and conflict. Societies, in general face a crisis of social cohesion. At the same time, with accelerated growth and high rate of innovation societies enter a period of great opportunities. Both addressing the multifaceted crisis and capitalizing the opportunities requires understanding on how global techno-social systems work. Although our understanding of specific mechanisms and their emergent consequences has been considerable advanced as the result of complexity research we still need to understand better how the specific mechanisms combine, the nature and emergent dynamics of multiple feedback loops which involve processes of different kinds such as social, financial, environmental etc. Our knowledge can be instrumental in both capitalizing on the opportunities and avoiding the crisis.

Global systems science approach allows us understanding how different processes of various natures e.g. economical, social, political, technological, biological and physical interact in a specific area of a social system, e.g. smart energy grids. The main pillars of the global systems approach are:
1) Strong, precise theories
2) Computer simulation models of real-life phenomena
3) Analysis of big data
4) Relevance to technology
5) Practical applications for policymaking and business
6) Interfacing with art

Why global systems?
The approach of global systems is trans-disciplinary. It provides the scientific base to understand how real life societal phenomena result from interaction of multiple processes. It has strong empirical base in modern methods of data collection, especially big data. It is relevant to technology. It provides clear answers for policymakers and businesses. It uses art to communicate findings, to enhance creativity and as a complementary perspective on the social processes.

Strong, precise theories of how processes of different nature interact in social systems
Theories form the core of science. Theories traditionally developed in the social sciences (with the exception of economy), have overwhelmingly been qualitative. Rapid growth of computer simulations and recent availability of big data are transforming the nature of the theories in the social sciences. The social sciences increasingly focus on the dynamic, rather than static description of social phenomena as social models become increasingly precise and are expressed in computational models or formulas. The approach of complex systems has used computer simulations mostly to explore a single process (e.g. public opinion, synchronization in neural systems) and it has concentrated on explaining how complex properties at the system level emerge for the interactions of the elements of the system. The approach of global systems goes beyond the focus on a single process and it concentrates on understanding how the dynamics of real-world phenomena results from the interaction of multiple processes of different natures in the system that produces the phenomena.

Computer simulation models of real-world phenomena
Computer simulation models represent the primary tool of the global systems approach. Such models both precisely describe the mutual interdependence of various processes and allow studying emergent consequences of the interaction of these processes. Computer simulations also are the tools for conditional predictions for science, business and policy-making. Simulations unveil conditional scenarios of events resulting from interventions and decisions. Before making a decision, the stakeholder can examine short and long terms complex consequences of alternative decisions.

Analysis of empirical data, especially big data.
To be useful, a theory must be verified by data. New technology offers revolutionary new types of data that can be used to form and verify theories. Internet, mobile technologies, sensors and cameras provide an unprecedented amount of data, so-called big data. These data require new methods of analysis, for example dynamic network analysis, geographical analysis, massive content analysis etc. Visualization is important tool of analyzing the data. New visualization methods are needed to visualize terabytes or petabytes of data or interactions between hundreds of millions of individuals. Big data analysis is no longer the exclusive domain of computer science mathematics and physics and is being adopted as the method by the social sciences. In fact the 2014 American Psychological Science convention is devoted to big data.
Analysis of big data is also at the heart of modern businesses and politics. Big data represent one of the most valuable commodities for today's businesses. Capacity for analyzing big data lags far behind the availability of large datasets. Establishing big data analysis expertise group at Global Systems Center will enable creation of links with other excellence centers in this domain in academia, businesses and policymakers. Training students in big data analysis opens career path for FAU graduates both in academia and outside of it.

Relevance to technology
Current science undergoes pronounced change, in large part due to the rapid development of technology. Technology strongly impacts almost all areas of social life, transforms how businesses and institutions are functioning, and becomes the main driving force of economy. Technology itself also changed in a very significant way. The current technology is to large extent social. Such cutting edge areas as social networking (e.g. Facebook or Twitter), mobile technology, voice recognition or interactive intelligent environment are examples where the technology is used for social processes. The goldmine of today’s business, big data, is in fact, data about human behavior. The design of modern technology starts with designing how users will interact with the technology.
It is also the case that technology has a strong impact on almost every aspect of social life. Societies, in fact, have become techno-social systems, composed of humans, devices and sensors interacting by means of technology such as Internet, mobile devices (smartphones and tablets), short and medium range local communication (Bluetooth and Wi-Fi). The social processes involve purely social interactions, interactions of humans mediated by technology, interaction with humans with devices (e.g. automated call centers, players interacting with bots in games, humans interacting with algorithms in electronic trading), and devices interacting with other devices. The involvement of technology changes, thus, social processes in a profound way. Global systems approach offers an integrated perspective from which we can understand properties of complex techno – social systems.

Practical applications for policymaking and business

Sources of funding for pure sciences are drying up. The funds, however, for projects that are perceived as benefiting society may be increasing. Social issues such as: climate instability, energy, depleting resources (e.g. water shortage) conflicts and swings of economy are embedded in a web of interdependent processes. Often decisions have unseen undesirable consequences. For example, no one predicted that eco-friendly decision to increase the production of biofuels would lead to food shortages in several African and Asian countries. Decision-makers understand that they need science to inform them of consequences of various decisions and to help them develop solutions to problems they are trying to solve.
Society wants to know how the tax money spent on science is producing benefits for the society. Policymakers are well aware of that. There is increased pressure on science to produce results that can be shown to be directly applicable to the real world. All the real-world phenomena are dynamics and involve a multitude of interacting processes. Global system science can and should lead to practical applications for policymaking and businesses. The ability to use science in business and social applications also can pave the way for FAU graduates to find attractive employment.

Interfacing with art
Science has built an impressive body of knowledge that potentially is of great interest for society and can benefit the society in almost all the aspects of its functioning. Unfortunately, science is not good in communicating its knowledge. Art, however, specializes in effective communication. The liaison between science and art is central for communication of scientific results to policymakers and the general public. There other benefits of science and art working together. Including artistic and scientific teams increases the creativity of such teams. Art offers the complementary to science perspective on social issues.

In my opinion the most challenging issues that can be addressed by global systems science are:
Social cohesion vs. radicalization
Social Innovation
Conflict and sustainable peace
Social mechanisms underlying finance and economy
How to increase effectiveness of bottom-up social processes
Art and science as complementary ways of understanding and influencing the social dynamics

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