3 joint papers in a special issue of EPJ Special Topics on "Participatory Science and Computing for Our Complex World"

In special issue of the European Physical Journal (Special Topics) I am a co-author on three papers:

Paolucci,  Mario et al. (2012) Towards a Living Earth Simulator.  European Physical Journal Special Topics, 214(1):77-108. DOI 10.1140/epjst/e2012-01689-8.



Abstract

The Living Earth Simulator (LES) is one of the core components of the FuturICT architecture. It will work as a federation of methods, tools, techniques and facilities supporting all of the FuturICT simulation-related activities to allow and encourage interactive exploration and understanding of societal issues. Society-relevant problems will be targeted by leaning on approaches based on complex systems theories and data science in tight interaction with the other components of FuturICT. The LES will evaluate and provide answers to real-world questions by taking into account multiple scenarios. It will build on present approaches such as agent-based simulation and modeling, multiscale modelling, statistical inference, and data mining, moving beyond disciplinary borders to achieve a new perspective on complex social systems.

Buckingham Shum, Simon et al. (2012) Towards a Global Participatory Platform: Democratising Open Data, Complexity Science and Collective Intelligence.  European Physical Journal Special Topics, 214(1):109-152. DOI 10.1140/epjst/e2012-01690-3.




Abstract

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project’s own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed.

Deffuant, Guillaume et al. (2012)  Data and models for exploring sustainability of human well-being in global environmental change.  European Physical Journal Special Topics, 214(1):519-545. DOI 10.1140/epjst/e2012-01704-2.

Abstract

This position paper proposes a vision for the research activity about sustainability in global environmental change (GEC) taking place in the FuturICT flagship project. This activity will be organised in an “Exploratory”, gathering a core network of European scientists from ICT, social simulation, complex systems, economics, demographics, Earth system science. These research teams will collaborate in building a self-organising network of data sources and models about GEC and in using new facilities fostering stakeholder participation. We develop examples of concrete directions for this research: world wide virtual population with demographic and some economic descriptors, ecosystem services production and distribution, governance systems at various scales.

 There are many other interesting papers there (see the issue), basically position papers underlying the FuturICT proposal.

Slides of talk: on "Social Complexity"

 Given at the Interdisciplinary Workshop on 31st October 2012, Manchester (http://manchester-complexity.blogspot.co.uk/2012/10/interdisciplinary-workshop-on-complex.html)

Slides at: http://www.slideshare.net/BruceEdmonds/social-complexity

Published Paper: "Complexity and Context Dependency" in journal Foundations of Science

at: http://www.springerlink.com/content/658664733q7571qu/

Complexity and Context-Dependency

Bruce Edmonds

Abstract

It is argued that given the “anti-anthropomorphic” principle—that the universe is not structured for our benefit—modelling trade-offs will necessarily mean that many of our models will be context-specific. It is argued that context-specificity is not the same as relativism. The “context heuristic”—that of dividing processing into rich, fuzzy context-recognition and crisp, conscious reasoning and learning—is outlined. The consequences of accepting the impact of this human heuristic in the light of the necessity of accepting context-specificity in our modelling of complex systems is examined. In particular the development of “islands” or related model clusters rather than over-arching laws and theories. It is suggested that by accepting and dealing with context (rather than ignoring it) we can push the boundaries of science a little further. 

Keywords  Complexity – Context – Generality – Models – Pragmatics – Anthropomorphism 

Edmonds, B. (2013) Complexity and Context-Dependency. Foundations of Science, 18(4):745-755. DOI: 10.1007/s10699-012-9303-x (previous version at http://cfpm.org/cpmrep209.html)

New Paper Published: "Modelling Belief Change in a Population Using Explanatory Coherence", Advances in Complex Systems, http://dx.doi.org/10.1142/S0219525912500853

This is an alternative approach to models of mutual influence, based upon a model of belief change and the consistency/coherency between different beliefs.  It suggests some different hypotheses compared to Guillaume-Salah style models.  If anyone knows of any good data that might help check the realism of this model, please tell me about it (or just do it yourself).

Edmonds, B. (2012) Modelling Belief Change in a Population Using Explanatory Coherence, Advances in Complex Systems, 15(6). (10.1142/S0219525912500853) 

 The Link to the WorldSci page is: http://www.worldscientific.com/doi/abs/10.1142/S0219525912500853

BRUCE EDMONDS, Advs. Complex Syst., 15, 1250085 (2012) [15 pages] DOI: 10.1142/S0219525912500853

MODELING BELIEF CHANGE IN A POPULATION USING EXPLANATORY COHERENCE

Abstract

A simulation model that represents belief change within a population of agents who are connected by a social network is presented based on Thagard's theory of explanatory coherence. In this model there are a fixed number of represented beliefs, each of which are either held or not by each agent. These are conceived of existing against a background of a large set of (unrepresented) shared beliefs. These beliefs are to different extents coherent with each other — this is modeled using a coherence function from possible sets of core beliefs to [-1, 1]. The social influence is achieved through gaining of a belief across a social link. Beliefs can be lost by being dropped from an agent's store. Both of these processes happen with a probability related to the change in coherence that would result in an agent's belief store. A resulting measured "opinion" can be retrieved in a number of ways, here as a weighted sum of a pattern of the core beliefs — opinion is thus an outcome and not directly processed by agents. This model suggests hypotheses about group opinion dynamics that differ from that of many established models.

Keywords: Simulation; coherence; consistency; opinion dynamics; belief revision

(Earlier version at: http://cfpm.org/cpmrep185.html)

Slides from ESSA Summer School: "Personal understanding and publically useful knowledge in Social Simulation"

My talk at the ESSA summer school in Toulouse (http://www.irit.fr/essa-summer-school-2012), which was very enjoyable, some great up-and-coming researchers and a great location/organisation.

Talk Abstract:

There are two different ways in which social simulation can help a researcher - by honing their intuition about how certain models and mechanisms (roughly what Polanyi meant by "Personal Knowledge") and in demonstrating hypotheses that might be interesting and relevant to other researchers in the field (roughly what Popper meant by "Objective Knowledge").  Both are valid goals and useful, indeed I would argue both are essential to real progress in social simulation.  However, too often, these are conflated and confused, to the detriment of social simulation.  This talk aims to clearly distinguish between the two modes, including the different ways of obtaining them, their different (and complementary) uses as well as when and how these are appropriate to communicate to others.  In short a "model" of simulation usefulness is outlined with implications for the method of social simulation.

Slides at: http://www.slideshare.net/BruceEdmonds/personal-understanding-and-publically-useful-knowledge-in-social-simulation

Invited Talk at iEMMs 2012: "Context in Environmental Modelling - the room around the elephant"

This paper is related to the papers:

• Edmonds, B. (in press, 2013) Complexity and Context-dependency. Foundations of Science. (http://cfpm.org/cpmrep209.html)
• Edmonds, B. (2012) Context in Social Simulation: why it can't be wished away.  Computational and Mathematical Organization Theory, 18(1):5-21. (http://cfpm.org/cpmrep210.html)

but covers new topics and illustrations, working towards a more general formulation of the key problem and possible responses.

The slides are at: http://www.slideshare.net/BruceEdmonds/context-in-environmental-modelling-the-room-around-the-elephant

There is a video at: http://141.65.7.51/videos/video/35/ (last half of it)

Abstract:

Behaviour in society and the responses from the environment are both highly context-dependent.  There is a lot of evidence that hyman cognition and behaviour depends sharply on the percieved context.  Human collective and social behaviour is even more so, indeed may be structured around co-determined contexts that are then entrenched within our training, infrastructure and habits.  Similarly ecological niches, where species adapt to each other can be highly specific to a particular set of environmental affordences.  The response to a pertabation (e.g. reduction of a resource or introduction of a new species) depends highly on the environmental context.

However, to a very large extent, our formal models of the environment and of our interaction with the environment are context-free.  It is often simply assumed that the variations due to specific contexts can be dealt with as a kind of "noise" to a main trend or interaction.  Whilst this maybe sometimes the case, this assumption is rarely justified by any evidence or indeed convincing argument .  Often it seems that context is ignored simply because it seems too difficult to do otherwise, so work proceeds simply on the hope that context-dependency can be treated as a kind of noise.  Other strategies to avoid the issue of context include keeping to within a single, very restricted context (which prevents any general conclusions) or remaining in the world of analogy and natural language discourse (where context-dependency is masked by the innate ability of humans to reapply analogies on the fly). I argue that this must often not be the case and that a collection of context dependent interactions if treated in this way, can result in very different outcomes, especially when one needs to scale any conclusions.

I then seek to show some possible ways forward, ways to include some of the context-dependency in our techniques and models.  These include kinds of agent-based modelling that include context-awareness in the agents and actors, kinds of data-mining that could be used to search for patterns in a context-dependent manner, and new techniques from the field of visual analytics to visualise and interact with data via a visual interface in a context-friendly manner.

The video of my talk at Bath on "Complexity and Context Dependency"

As part of the one-day IOP workshop on the 19th December in Bath on "Complexity of Complexity"

Videos and slides from that day available from:
    http://www.bath.ac.uk/sps/news/news_0010.html

Network for Computational Modeling for SocioEcological Science (CoMSES Net)

The Network for Computational Modeling for SocioEcological Science (CoMSES Net) is based on the OpenABM.org site but extended to a network with wider scope and aims.  CoMSES has just been announced along with an invitation for people to register and apply for full membership.  Their aims are close to my heart...

COMSES Net will serve as a self-organized community of practice and a conduit to expedite knowledge exchange for computational modeling in SES. It will seek to grow scientific infrastructure so as to better serve research that uses computational modeling by:

• establishing an interactive, online library for computational models (including for review of models associated with publications) and associated standard data testbeds for model evaluation;
• promoting a common standard for model description;
• developing educational curricula for embedding modeling and computational thinking in the normal practice of social and natural science.
• collaborating with journals and other scientific publishing venues to promote the exchange of knowledge about modeling concepts and methods for SES, establish protocols for peer review of computational models, and ensure that scientists creating computational models for SES research receive intellectual credit for their work.

 For more details see:
    http://www.openabm.org/page/comses-net