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
6 Jul 2012
3 Jul 2012
Invited Talk at iEMMs 2012: "Context in Environmental Modelling - the room around the elephant"
This paper is related to the papers:
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.
- 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.
11 Feb 2012
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
Videos and slides from that day available from:
http://www.bath.ac.uk/sps/news/news_0010.html
4 Jan 2012
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:
http://www.openabm.org/page/comses-net
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.
http://www.openabm.org/page/comses-net
19 Dec 2011
Slides from my Bath IOP talk on "Complexity and Context-Dependency", 19th Dec 2011
This version of the talk goes more into ways of looking for context in social science data.
http://www.slideshare.net/BruceEdmonds/complexity-and-contextdependency-version-for-bath-iop-seminar
http://www.slideshare.net/BruceEdmonds/complexity-and-contextdependency-version-for-bath-iop-seminar
15 Dec 2011
Kick-off meeting of the "Crime and Corruption Exploratory", Rome 25-27th Jan 2012
Kick-off meeting
‘Crime and Corruption Exploratory’
Rome, January 25 to 27, 2012
Docs about crimEx
https://docs.google.com/open?
https://docs.google.com/open?
Draft Scheduling
on the 25, start at 14:30, until around 18:30
Introduction to themes: around CCE
CCE and Network
on the 26, 10:30-16:30
Working Groups
Governance
Resources
Logistic
In the afternoon: plenary sessionon the 27, 10:30-18:30
What to do now: working groups on strategic choices and funding
In the afternoon: plenary session
Registration. (If you have not already done, but you're interested in participating , please register: the policy with which it handles reservations is first-in first-out …)
On the web site http://
you will find a page called Registration form, that allows you to automatically register to the event. Registration is free. After the confirmation of the registration you'll receive the information on the logistic of the event.
22 Nov 2011
A one-day inter-disciplinary seminar on "Complexity of Complexity", Bath 19th Dec.
The Complexity of Complexity
A one-day inter-disciplinary seminar
December 19th 2011, 10.30-3.30 at the University of Bath
Speakers:
Peter Allen, Complex Systems Research Centre, Cranfield
“Evolutionary complexity and the Real
World”
Bruce Edmonds, Centre for Policy Modelling, Manchester Metropolitan
University
“Complexity and Context-Dependency”
Chaired by:
Dr Jean Boulton, Department of Social and Policy Sciences, University of
Bath
Complexity theory has been embraced by a wide range of disciplines -
physics, biology, earth sciences and economics, strategy development, urban
planning and climate modelling to name but a view. It developed, through the
20th century, out of early systems thinking, non-equilibrium thermodynamics
and evolutionary theory. But is there one theory or many? What are the
assumptions underpinning differing approaches? Are some applications more
metaphorical than scientific? What is the worldview implied by complexity? Is
complexity necessarily about modelling?
This seminar, sponsored by the Institute of Physics Nonlinear and
Complex Physics group, seeks to provide a forum to explore the way complexity
is understood by different disciplines and provide the opportunity for
cross-disciplinary learning and debate sparked by our two eminent speakers.
The event is free; to book, please email Jean Boulton on j.g.boulton@bath.ac.uk
stating the focus of your interest. Places are restricted to 40.
17 Nov 2011
Google Citations
Google now has a basic citations page you can build very easily (Google suggests the list of your citations and you edit these to remove the few spurious ones etc.)
Mine is at: http://scholar.google.com/citations?hl=en&user=uYuZ1VEAAAAJ
Mine is at: http://scholar.google.com/citations?hl=en&user=uYuZ1VEAAAAJ
2 Nov 2011
I have started a new blog on "Simulating the social processes of science"...
... to coincide with publication of the special section of JASSS on the same theme (see blog for details).
The blog is at:
http://simsocsci.blogspot.com/
The blog is at:
http://simsocsci.blogspot.com/
24 Oct 2011
Special Issue of "Simulation" in Jan 2012 on ABS of Complex Social Systems
There will be a Special Issue of the Journal Simulation in Jan 2012 on the topic:
Agent-Based Simulation of Complex Social Systems
Edited by
Adolfo López-Paredes
|
|
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Franziska
Klügl
|
|
|
Bruce
Edmonds
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The Papers will be:
- Heppenstall, Implementing Comprehensive Offender Behaviour in a Realistic Agent-Based Model of Burglary
- Troitzsch, Simulating Communication and Interpretation as Means of Interaction in Human Social Systems
- Son, Simulation-Based Workforce Assignment Considering Position in a Social Network
- Giardini, Gossip for Social Control in Natural and Artificial Societies
- Zhou, On Fidelity and Model Selection for Discrete Event Simulation
- Topcuoglu, A New 3-D Wireless Multimedia Sensor Network Simulation Environment for Connected Coverage Problems
- Ma, Evaluation of integrated application of intelligent
transportation systems (ITS) technologies using stochastic incident
generation and resolution modeling
21 Oct 2011
13 Oct 2011
Paper published: Disaggregating quality judgements
Edmonds, B. (2011) Disaggregating
quality judgements. Mind & Society 10(2):169-180. (http://www.springerlink.com/content/67500t946828u1n2)
(Original discussion paper: http://cfpm.org/cpmrep204.html)
Abstract:
The notion of quality is analysed for its functional roots as a social heuristic for reusing others’ quality judgements and hence aiding choice. This is applied to the context of academic publishing, where the costs of publishing have greatly decreased, but the problem of finding the papers one wants has become harder. This paper suggests that instead of relying on generic quality judgements, such as those delivered by journal reviewers, that the maximum amount of judgemental information be preserved and then made available to potential readers to help them find papers that meet their particular needs. The suggestion is that: multidimensional quality data be captured on review of papers, this information is stored on a database, and then used to filter papers according to the criteria set by the searcher—personalising the quality filter. In other words the quality judgements and subsequent use are maintained in a disaggregated form, maintaining the maximum informational context of the judgements for future use. The advantages, disadvantages, challenges and possible variations of this proposal are discussed.
Abstract:
The notion of quality is analysed for its functional roots as a social heuristic for reusing others’ quality judgements and hence aiding choice. This is applied to the context of academic publishing, where the costs of publishing have greatly decreased, but the problem of finding the papers one wants has become harder. This paper suggests that instead of relying on generic quality judgements, such as those delivered by journal reviewers, that the maximum amount of judgemental information be preserved and then made available to potential readers to help them find papers that meet their particular needs. The suggestion is that: multidimensional quality data be captured on review of papers, this information is stored on a database, and then used to filter papers according to the criteria set by the searcher—personalising the quality filter. In other words the quality judgements and subsequent use are maintained in a disaggregated form, maintaining the maximum informational context of the judgements for future use. The advantages, disadvantages, challenges and possible variations of this proposal are discussed.
19 Sept 2011
CfP: Workshop on Modelling Policy-making (MPM 2011)
Vienna, Dec 12 or 13th 2011.
In conjunction with
The 24th International Conference on Legal Knowledge and Information Systems (JURIX 2011)
Submission Focus:
The workshop invites submissions of original research about the application of ICT to the early phases of the policy cycle, namely those before the legislation is fixed by the legislators: agenda setting, policy analysis, and lawmaking. The research should seek to address the gap noted above. The workshop focusses particularly on using and integrating a range of subcomponents – information extraction, processing, representation, modelling, simulation, reasoning, and argument – to provide policy making tools to the public and public administrators.
Deadline: 24th October
http://wyner.info/LanguageLogicLawSoftware/index.php/2011/09/18/workshop-on-modelling-policy-making/
15 Sept 2011
My ECCS 2011 Poster: Using Data Sets to Simulate Evolution within Complex Environments (A0 Poster)
Poster:
http://www.slideshare.net/BruceEdmonds/using-data-sets-to-simulate-evolution-within-complex-environments-poster
Abstract:
An agent-based model of evolution and adaption is presented with complex genomes, sexual and asexual reproduction. However, unlike other models, this has a purposefully complex environment. Individuals are spread over a 2D space upon which is projected a complex data set derived from observations of the real world. Energy extraction for the purposes of life and reproduction is achieved by the match between the genome and the data in its locality. In this model different genomes develop to exploit different parts of the space, with some genomes acquiring a greater generality than others. This model can be used to explore the trade-offs inherent between diversity, specialization and inter-breeding among individuals.
http://www.slideshare.net/BruceEdmonds/using-data-sets-to-simulate-evolution-within-complex-environments-poster
Abstract:
An agent-based model of evolution and adaption is presented with complex genomes, sexual and asexual reproduction. However, unlike other models, this has a purposefully complex environment. Individuals are spread over a 2D space upon which is projected a complex data set derived from observations of the real world. Energy extraction for the purposes of life and reproduction is achieved by the match between the genome and the data in its locality. In this model different genomes develop to exploit different parts of the space, with some genomes acquiring a greater generality than others. This model can be used to explore the trade-offs inherent between diversity, specialization and inter-breeding among individuals.
My talk at CoDyn@ECCS 2011: Modelling Belief Change in a Population Using Explanatory Coherence
Slides:
http://www.slideshare.net/BruceEdmonds/modelling-belief-change-in-a-population-using-explanatory-coherence
Abstract:
A simulation model is presented that represents belief change, based on Thagard’s theory of explanatory coherence, within a population of agents who are connected by a social network. In this model there are a fixed number of represented beliefs, each of which are either held or not by each agent. These beliefs are to different extents coherent with each other – this is modelled using a coherence function from possible sets of core beliefs to [-1,1]. The social influence is achieved through gaining of a belief from another agent 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. Results suggest that a reasonable rate of copy and drop processes and a well connected network are required to achieve consensus, but given that, the approach is effective at producing consensuses for many compatibility functions. However, there are some belief structures where this is difficult.
http://www.slideshare.net/BruceEdmonds/modelling-belief-change-in-a-population-using-explanatory-coherence
Abstract:
A simulation model is presented that represents belief change, based on Thagard’s theory of explanatory coherence, within a population of agents who are connected by a social network. In this model there are a fixed number of represented beliefs, each of which are either held or not by each agent. These beliefs are to different extents coherent with each other – this is modelled using a coherence function from possible sets of core beliefs to [-1,1]. The social influence is achieved through gaining of a belief from another agent 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. Results suggest that a reasonable rate of copy and drop processes and a well connected network are required to achieve consensus, but given that, the approach is effective at producing consensuses for many compatibility functions. However, there are some belief structures where this is difficult.
My talk at Policy Modelling@ECCS 2011: Four different views of a policy model : an analysis and some suggestions
Slides:
http://www.slideshare.net/BruceEdmonds/four-different-views-of-a-policy-model-an-analysis-and-some-suggestions
Abstract:
A policy model has (at least) four different interpretations: (a) intention: the intention/interpretation of the simulation designer/programmer, (b) validation: the meaning established by the validation of the model in terms of the mapping(s) to sets of evidence, (c) use: the meaning established as a result of the use of a model in a policy making/advice context and (d) interpretation: the narrative interpretation of the policy maker/advisor when justifying decisions made where this refers to a policy model.
These four different interpretations are loosely connected via social processes. The relation between intention and validation is relatively well discussed in the context of “scientific” model specification and development. The relation between use and interpretation has been discussed in a number of specific contexts. However when and how a relationship between the scientific world of intention/validation and the policy world of use/interpretation are established in practice is an area with little active research.
Both personal experience and philosophical considerations suggest that these two worlds are very different in terms of both purpose and method. However this does not mean that there cannot be any well-founded connection between them. The key question is understanding the social processes of how this can happen, what are the conditions that facilitate it happening and what is the nature of the relationship between the four views when it does happen.
Interestingly these issues have been faced and extensively discussed in the field of Artificial Intelligence, which has confronted the distinction between meaning of internal models (loosely, the beliefs of an agent about its environment) in these four ways. The field of AI has not come up with a final solution to these problems, and is itself divided into those that inhabit separate approaches that adopt a subset of these approaches to model meaning. However it is suggestive of some ways forward, namely:
• a recognition of the problem that there are these different ways of attributing meaning to a policy model (and hence avoid some common errors derived from conflating these four views);
• symbol grounding in the sense of learning meanings through repeated use and adjustment (either in response to validation or interpretation views or both);
• and the observation of scientific-policy interaction as it actually occurs (e.g. an ethnographic study of scientist/policy advisor interaction).
Some developments in the area of participatory policy modelling can be seen as forays into this arena, albeit without structured assessment.
http://www.slideshare.net/BruceEdmonds/four-different-views-of-a-policy-model-an-analysis-and-some-suggestions
Abstract:
A policy model has (at least) four different interpretations: (a) intention: the intention/interpretation of the simulation designer/programmer, (b) validation: the meaning established by the validation of the model in terms of the mapping(s) to sets of evidence, (c) use: the meaning established as a result of the use of a model in a policy making/advice context and (d) interpretation: the narrative interpretation of the policy maker/advisor when justifying decisions made where this refers to a policy model.
These four different interpretations are loosely connected via social processes. The relation between intention and validation is relatively well discussed in the context of “scientific” model specification and development. The relation between use and interpretation has been discussed in a number of specific contexts. However when and how a relationship between the scientific world of intention/validation and the policy world of use/interpretation are established in practice is an area with little active research.
Both personal experience and philosophical considerations suggest that these two worlds are very different in terms of both purpose and method. However this does not mean that there cannot be any well-founded connection between them. The key question is understanding the social processes of how this can happen, what are the conditions that facilitate it happening and what is the nature of the relationship between the four views when it does happen.
Interestingly these issues have been faced and extensively discussed in the field of Artificial Intelligence, which has confronted the distinction between meaning of internal models (loosely, the beliefs of an agent about its environment) in these four ways. The field of AI has not come up with a final solution to these problems, and is itself divided into those that inhabit separate approaches that adopt a subset of these approaches to model meaning. However it is suggestive of some ways forward, namely:
• a recognition of the problem that there are these different ways of attributing meaning to a policy model (and hence avoid some common errors derived from conflating these four views);
• symbol grounding in the sense of learning meanings through repeated use and adjustment (either in response to validation or interpretation views or both);
• and the observation of scientific-policy interaction as it actually occurs (e.g. an ethnographic study of scientist/policy advisor interaction).
Some developments in the area of participatory policy modelling can be seen as forays into this arena, albeit without structured assessment.
My talk at NESS@ECCS 2011: Mundane Rationality as a basis for modelling and understanding behaviour within specific contexts
Slides:
http://www.slideshare.net/BruceEdmonds/mundane-rationality-as-a-basis-for-modelling-and-understanding-behaviour-within-specific-contexts-9251997
Abstract:
The paper starts out by pointing out the context-dependency of human cognition and behaviour, pointing out that (a) human behaviour can change sharply across contexts but also that (b) behaviour within a given context can sometimes be described in relatively simple terms . It thus argues against a grand theory of rationality that seeks to explain and/or generate human behaviour across of contexts. Rather it suggests an alternative approach whereby "mundane" accounts of rationality are used which are specific to a limited number of contexts. Such an approach has its particular difficulties, but allows the integration of narrative accounts of possible behaviours using a variety of social mechanisms at the micro level with comparisons with aggregate macro data. It is noted that in the resulting simulations that equilibria are simply not relevant within plausible timescales.
http://www.slideshare.net/BruceEdmonds/mundane-rationality-as-a-basis-for-modelling-and-understanding-behaviour-within-specific-contexts-9251997
Abstract:
The paper starts out by pointing out the context-dependency of human cognition and behaviour, pointing out that (a) human behaviour can change sharply across contexts but also that (b) behaviour within a given context can sometimes be described in relatively simple terms . It thus argues against a grand theory of rationality that seeks to explain and/or generate human behaviour across of contexts. Rather it suggests an alternative approach whereby "mundane" accounts of rationality are used which are specific to a limited number of contexts. Such an approach has its particular difficulties, but allows the integration of narrative accounts of possible behaviours using a variety of social mechanisms at the micro level with comparisons with aggregate macro data. It is noted that in the resulting simulations that equilibria are simply not relevant within plausible timescales.
My talk at ECCS2011: Using a Data-Integration Model to Stage Abstraction in Voter Turnout
Slides:
http://www.slideshare.net/BruceEdmonds/using-a-dataintegration-model-to-stage-abstraction-in-voter-turnout
Abstract:
A simulation model is presented that represents belief change, based on Thagard’s theory of explanatory coherence, within a population of agents who are connected by a social network. In this model there are a fixed number of represented beliefs, each of which are either held or not by each agent. These beliefs are to different extents coherent with each other – this is modelled using a coherence function from possible sets of core beliefs to [-1,1]. The social influence is achieved through gaining of a belief from another agent 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. Results suggest that a reasonable rate of copy and drop processes and a well connected network are required to achieve consensus, but given that, the approach is effective at producing consensuses for many compatibility functions. However, there are some belief structures where this is difficult.
http://www.slideshare.net/BruceEdmonds/using-a-dataintegration-model-to-stage-abstraction-in-voter-turnout
Abstract:
A simulation model is presented that represents belief change, based on Thagard’s theory of explanatory coherence, within a population of agents who are connected by a social network. In this model there are a fixed number of represented beliefs, each of which are either held or not by each agent. These beliefs are to different extents coherent with each other – this is modelled using a coherence function from possible sets of core beliefs to [-1,1]. The social influence is achieved through gaining of a belief from another agent 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. Results suggest that a reasonable rate of copy and drop processes and a well connected network are required to achieve consensus, but given that, the approach is effective at producing consensuses for many compatibility functions. However, there are some belief structures where this is difficult.
3 Aug 2011
My talk @ 2011 ESSA Summer School: "The Impossibility of Social Simulation"
Video is at:
http://www.youtube.com/watch?v=ZmAKbI3wqOU
Other information (slides, abstract) posted previously:
http://bruceedmonds.blogspot.com/2011/07/simulation-summer-school-slides.html
http://www.youtube.com/watch?v=ZmAKbI3wqOU
Other information (slides, abstract) posted previously:
http://bruceedmonds.blogspot.com/2011/07/simulation-summer-school-slides.html
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