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
19 Dec 2011
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
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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
25 Jul 2011
Diagrams of Phillips' Fluid Mechanical Model of the economy
 |
| First of the real thing... |
 |
| ...then as a cartoonist in Punch depicted it! |
A brief interview of me by David Hales
At the ESSA summer school in Surrey.
http://www.youtube.com/watch?v=kPHTFU7Vi0A
To see other interviews, including Paul Omerod, Warrent Thorngate and Edmund Chattoe-Brown go to David's youtube page http://www.youtube.com/user/daphal
http://www.youtube.com/watch?v=kPHTFU7Vi0A
To see other interviews, including Paul Omerod, Warrent Thorngate and Edmund Chattoe-Brown go to David's youtube page http://www.youtube.com/user/daphal
21 Jul 2011
A paper on simulation experiment design for social simulation
Opening the ‘Black Box’ of Simulations: Transparency of Simulation Models and Effective Results Reports Through the Systematic Design of Experiments
Iris Lorscheid
Hamburg University of Technology
Heine Bernd-Oliver
affiliation not provided to SSRN
Matthias Meyer
Technical University Hamburg-Harburg (TUHH)
Abstract:
Many still view simulation models as a black box. This paper argues that perceptions could change if the systematic design of experiments (DOE) for simulation research was fully realized. DOE can increase (1) the transparency of simulation model behavior and (2) the effectiveness of reporting simulation results. Based on DOE principles, we develop a systematic procedure to guide the analysis of simulation models as well as concrete templates for sharing the results. A simulation model investigating the performance of learning algorithms in an economic mechanism design context illustrates our suggestions. Overall, the proposed systematic procedure for applying DOE principles complements current initiatives for a more standardized simulation research process.
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1860904
Bruce Edmonds
Iris Lorscheid
Hamburg University of Technology
Heine Bernd-Oliver
affiliation not provided to SSRN
Matthias Meyer
Technical University Hamburg-Harburg (TUHH)
Abstract:
Many still view simulation models as a black box. This paper argues that perceptions could change if the systematic design of experiments (DOE) for simulation research was fully realized. DOE can increase (1) the transparency of simulation model behavior and (2) the effectiveness of reporting simulation results. Based on DOE principles, we develop a systematic procedure to guide the analysis of simulation models as well as concrete templates for sharing the results. A simulation model investigating the performance of learning algorithms in an economic mechanism design context illustrates our suggestions. Overall, the proposed systematic procedure for applying DOE principles complements current initiatives for a more standardized simulation research process.
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1860904
Bruce Edmonds
19 Jul 2011
Simulation Summer School Slides
I am at the ESSA Summer School at Surrey University. I lasts the whole week.
All the slides (as they are uploaded) will be at:
http://www.simian.ac.uk/courses/essa-summer-school-2011/presentations
My talk (yesterday) was entitled "The Impossibility of Social Simulation" and you will find the slides at the above link.
Abstract:
It is often forgotten how difficult the task of a social simulator is. In this talk I start by discussing some of these difficulties. I move on to discussing some of trade-offs that are inevitable with social simulation, including that between relevance and rigour. These difficulties and trade-offs are related to the various possible purposes for the simulation of social phenomena including those of conceptual clarification, prediction, explanation and mechanism analysis. Those embarking on this complex and difficult task are exhorted not to fudge these issues, but to consider them carefully, make them explicit and accept the consequences of their choices.
All the slides (as they are uploaded) will be at:
http://www.simian.ac.uk/courses/essa-summer-school-2011/presentations
My talk (yesterday) was entitled "The Impossibility of Social Simulation" and you will find the slides at the above link.
Abstract:
It is often forgotten how difficult the task of a social simulator is. In this talk I start by discussing some of these difficulties. I move on to discussing some of trade-offs that are inevitable with social simulation, including that between relevance and rigour. These difficulties and trade-offs are related to the various possible purposes for the simulation of social phenomena including those of conceptual clarification, prediction, explanation and mechanism analysis. Those embarking on this complex and difficult task are exhorted not to fudge these issues, but to consider them carefully, make them explicit and accept the consequences of their choices.
7 Jul 2011
16 Jun 2011
My presentation at FuturICT meeting in Zurich 16th June 2011
On "Participatory Policy Modelling"
Slides at:
http://bruce.edmonds.name/slides/Participatory%20Policy%20Modelling%20-%20BE.ppt
Slides at:
http://bruce.edmonds.name/slides/Participatory%20Policy%20Modelling%20-%20BE.ppt
My talk at "Complexity of Evolutionary Processes Workshop" in Manchester
Using data sets to simulate evolution within complex environmentsBruce Edmonds
The talk suggests a way to investigate whether environmental complexity affects evolutionary processes. The suggestion is to use complex data sets that derive from the observation/measurement of natural systems. The data set is spread accross a space defined by two of the variables in the data set. The genome of individuals encode a model that tries to predict the outcome variable from the independent variables in the set. Resources in the model are gained by individuals local to a data point predicting the outcome variable better than its competitors. Once the contribution of resources to all individuals is decided, then an evolutionary process takes place, preferentially propogating and mating fitter individuals (so the less fit die). This is illustrated with an evolutionary model using the Cleveland Heart Disease Data Set. Evolution on this is compared to evolution on a data set with similar distributions of values for each variable but chosen independently of each other, so with the noise and shape of the original but without the complexity. Illustrative results showing that the change in environment significantly affects how evolution proceeds is exhibited and discussed. It is suggested that the same approach could be used to test the assumptions (e.g. the adequacy of a simple environment) in many models of evolutions, as well as investingating whe environmental complexity might affect evolution and what kind of complexity.
A talk at the IOP workshop:
http://www.theory.physics.manchester.ac.uk/~galla/ncpmeeting2011/ncpmeeting.html
My slides can be found at:
http://bruce.edmonds.name/slides/Complexity%20of%20evol%20processes%20-%20BE.ppt
The talk suggests a way to investigate whether environmental complexity affects evolutionary processes. The suggestion is to use complex data sets that derive from the observation/measurement of natural systems. The data set is spread accross a space defined by two of the variables in the data set. The genome of individuals encode a model that tries to predict the outcome variable from the independent variables in the set. Resources in the model are gained by individuals local to a data point predicting the outcome variable better than its competitors. Once the contribution of resources to all individuals is decided, then an evolutionary process takes place, preferentially propogating and mating fitter individuals (so the less fit die). This is illustrated with an evolutionary model using the Cleveland Heart Disease Data Set. Evolution on this is compared to evolution on a data set with similar distributions of values for each variable but chosen independently of each other, so with the noise and shape of the original but without the complexity. Illustrative results showing that the change in environment significantly affects how evolution proceeds is exhibited and discussed. It is suggested that the same approach could be used to test the assumptions (e.g. the adequacy of a simple environment) in many models of evolutions, as well as investingating whe environmental complexity might affect evolution and what kind of complexity.
A talk at the IOP workshop:
http://www.theory.physics.manchester.ac.uk/~galla/ncpmeeting2011/ncpmeeting.html
My slides can be found at:
http://bruce.edmonds.name/slides/Complexity%20of%20evol%20processes%20-%20BE.ppt
26 May 2011
CfP: SPECIAL ISSUE ON “SIMULATION AND LAW”
CfP: SPECIAL ISSUE ON “SIMULATION AND LAW”
Journal of Artificial Intelligence and Law
Editors: K.D. Ashley; G. Sartor; A. Oskamp.
ISSN: 0924-8463 (print version) ISSN: 1572-8382 (electronic version)
The Special Issue on “SIMULATION AND LAW” aims to promote
collaboration between the fields of agent-based simulation (ABS) and
the legal domain, bringing together ideas and researchers from both
communities.
The Journal of Artificial Intelligence and Law contains information on
theoretical or empirical studies in artificial intelligence, cognitive
psychology, jurisprudence, linguistics, or philosophy that address the
development of formal or computational models of legal knowledge,
reasoning, and decision making. It also includes in-depth studies of
innovative artificial intelligence systems that are being used in the legal
domain as well as gives space to studies that address the ethical and
social implications of the field of artificial intelligence and law.
The target of this Special Issue is to stimulate the interplay of both
disciplines, as well as to prompt a reflection exercise on the prospects
of using agent-based simulation to study socio-legal phenomena, as
well as the potential that such an interaction could have in law- and
policy-making processes.
IMPORTANT DATES/ DEADLINES
Abstract Submission: June 24th, Friday
Acceptance Notification: July 22nd, Friday
Paper Submission: November 4th, Friday
Acceptance Notification/Reviewers Reports: December 30th, Friday
Final Version Due: February 10th Friday
PUBLICATION AND SUBMISSION DETAILS
Submissions should be up to 16 pages maximum (including figures,
tables, bibliography, abstract etc) in the journal’s format (details can be
found in http://www.springer.com/computer/artificial/journal/10506 ).
REVIEW PROCESS
All submissions will go through a peer review process, with at least
two independent PC members reviewing each submission.
Following the first reviewing process, authors will be required to revise
their papers which will undergo a second review process before
publication in the journal.
ORGANIZING COMMITTEE
Giovanni Sartor
European University Institute, Law Department
Badia Fiesolana, Via dei Roccettini 9
Tel (office): +39-055-4685-528, Fax: +39-055-4685-200
Tel (secretary): +39-055-4685 275
E-mail: giovanni.sartor@eui.eu
http://www.iue.it/LAW/People/Faculty/CVs/sartor.shtml
Eunate Mayor
European University Institute, Law Department
Badia Fiesolana, Via dei Roccettini 9
I-50016 San Domenico di Fiesole (FI), ITALY
Tel (cell): +39-327-735-0409
E-mail: eunate.mayor@eui.eu
12 Apr 2011
An introductory talk: "What is Agent-Based Social Simulation?"
A talk I gave as part of the Methods@Manchester project.
Available (sound, links and slides) at:
http://www.methods.manchester.ac.uk/methods/abss/
Available (sound, links and slides) at:
http://www.methods.manchester.ac.uk/methods/abss/
25 Jan 2011
2nd CFP AEGS@AAMAS-2011: the uses of Agents for Education, Games and Simulations (long)
A call for papers for a workshop I'm involved in...
Rationale and technical description
===================================
Training for complex situations in human societies such as in education, business transactions, military operations, medical care and crisis management can be provided effectively using serious games and simulations. In these types of games and simulations the role of agents to model and simulate naturally behaving characters becomes more and more important. Especially in situations where the games are not just meant to provide fun, but are used to support the learning process it is important that the games achieve their goal and do not just distract (or entertain) the trainee.
A major aim of this workshop is to discuss how to model rational (or non-rational, but natural) behaving agents who are embedded in a social context with other characters and humans. This is especially important when both characters and humans can be pro-active but also have to react to the behaviour of others in their environment. Thus these characters should have some social conscience of themselves and others and base their decisions for actions on this knowledge. Of course social knowledge may consist of detailed knowledge such as that some person has been your long time friend and thus can be trusted to help you, but also general knowledge such as that society looks bad at people that cheat but adores people that grasp opportunities. Thus we aim to model also different levels of action and interactions. Both the operational ones such as gestures and general way of animating characters, the tactical decisions such as negotiation tactics when trying to get some help and long term strategies such as behaving cooperative towards your boss in order to secure a promotion. One of the interesting questions is how these should be modelled and how they interact? And how do current agent architectures support these models?
In general the technologies used in game engines and multi-agent platforms are not readily compatible due to some inherent differences of concerns. Where game engines focus on real-time aspects and thus propagate efficiency and central control, multi-agent platforms assume autonomy of the agents. And while the multi agent platforms offer communication facilities these can or should not be used when the agents are coupled to a game. So, although increased autonomy and intelligence may offer benefits for a more compelling game play and may even be necessary for serious games, it is not clear whether current multi agent platforms offer the facilities that are needed to accomplish this.
In this workshop we want to bring people together that address the particular challenges of using agent technology for games and simulations in particular for educational contexts.
The workshop will have four main themes:
1. Technical
What techniques are suitable for agents that are incorporated in educational contexts, games and simulations. How to balance intelligence and efficiency? How to couple the agents to the game/simulation and manage this coupling’s information flow? How to deal with the inherent real time nature of the game engine environment? How to couple long and short time interactions?
2. Conceptual
What information is available for the agents' use, either through the educational context, or from the system, through for example, the game or simulation engine? How can reaction to events be balanced with goal directed behaviour? How are ontological differences between information used by agents and information from the domain handled? How do we choose the actions of an agent? Too high level gives little control; too low level makes the agent inefficient.
3. Design
How do we design interactive systems containing intelligent agents? How do we determine what agents should do and should not do, such that local autonomy and story line are well balanced. How do we design the agents themselves that are embedded in other (possibly diverse) systems (including the behaviour authoring tools and methodologies)?
4. Education
It is also important that we introduce both the design and construction of these collaborative autonomous systems into the computer science curriculum and develop ways of encouraging their effective utilisation across the curriculum. Contributions to the workshop will be welcomed that provide a mixture of relevant theoretical and practical understanding of both the teaching and use of multi-agent systems in educational and entertainment research, together with practical examples of the use of such systems in real application scenarios. These will be written for students, teachers, producers, directors and other professionals who want to improve their understanding of the opportunities offered by the use of multi-agent systems in teaching and entertainment scenarios of all types.
Important Dates
===============
Deadline for receiving papers January 30 2011
Notification to authors February 27, 2011
Camera ready paper March 7, 2011
Workshop May 2 or 3, 2011
Submission Procedure
====================
The workshop welcomes submissions of original works relevant to the topics described above. This year, the workshop will accept submissions of both full papers (maximum 16 pages, LNCS format) and short papers (maximum 8 pages, LNCS format).
Short papers are encouraged as a mechanism for the timely reporting of interesting but preliminary work, that may not as yet have the level of evaluation or detail that would be expected for a regular paper. The program chairs may, at their discretion, accept papers that were submitted as regular papers as short papers, if the authors have explicitly agreed to this when registering their papers.
All accepted regular papers will receive a slot for oral presentation in the conference. The accepted short papers will serve as the basis for discussions during the workshop. If warranted they may be converted to regular papers for the post-proceedings by incorporating the results of these discussions.
Submissions will be peer reviewed rigorously and evaluated on the basis of adherence, originality, soundness, significance, presentation, understanding of the state of the art, and overall quality of their technical contribution. More details about the review process can be found in the conference page.
The papers should be formatted according to LNCS specification and submitted as PDF files. Instructions and templates can be found at
http://www.springer.de/comp/lncs/authors.html.
Final Papers must be submitted on A4 in PDF format. Your paper should not include page numbers.
All final manuscripts should be uploaded to easychair no later than
Sunday 30th January 2011
========================
The submission web site is http://www.easychair.org/conferences/?conf=AEGS-11
Submissions violating the formatting guidelines will be excluded from the reviewing process.
At least one author of all accepted papers is expected to attend the Workshop.
All accepted papers will be informally published in the Workshop proceedings, and the organisers intend to organize a LNCS publication of the workshop proceedings.
PC Committee
============
# Elisabeth Andre (DFKI, Germany)
# Juan Carlos Augusto (University of Ulster, UK)
# Paul Shueh-Min Chang, (National Tsing Hua University, Taiwan)
# Shu-Heng Chen, (National Cheng-Chi University, Taiwan)
# Bill Clancey (NASA, USA)
# Rosaria Conte (ISTC-CNR, Italy)
# Vincent Corruble (LIP6, France)
# Yves Demazeau (CNRS-LIG, Grenoble)
# Virginia Dignum (Technical University Delft, The Netherlands)
# Alexis Drogoul (LIP6, France)
# Bruce Edmonds (MMU, UK)
# Corinna Elsenbroich (University of Surrey, UK)
# Klaus Fischer (DFKI, Germany)
# Rachel E. Goshorn(Naval Postgraduate School, USA)
# Hiromitsu Hattori (Kyoto University, Japan)
# Annerieke Heuvelink (TNO, The Netherlands)
# Dirk Heylen (Univ of Twente, The Netherlands)
# Koen Hindriks (Delft University, The Netherlands)
# Jane Hsu (National Taiwan University, Taiwan)
# Toru Ishida (Kyoto University, Japan)
# Wander Jager (Groningen University, The Netherlands)
# Lewis Johnson (Alelo Inc., USA)
# Gal A. Kaminka (Bar Ilan University, Israel)
# Petros Kefalas (CITY Institute/Sheffield University GR)
# Irving King (Chinese University of Hong Kong, HK)
# Yasuhiko Kitamura (Kwansei Gakuin University)
# Stefan Kopp (University of Bielefeld, Germany)
# Mike van Lent (SOAR technology, USA)
# Michael Lewis (University of Pittsburg, USA)
# MeiYii Lim (Heriot-Watt University, UK)
# Chin-Yew Lin (Microsoft Research Asia, China)
# Shou-De Lin, (National Taiwan University, Taiwan)
# Simon Lynch (Univ. of Teeside, UK)
# Eleni Mangina (Phelan, University College Dublin, Ireland)
# Stacy Marsella, (ISI, Univ of Southern California, USA)
# Michael Mateas, (University of California at Santa Cruz, USA)
# Riichiro Mizoguchi (Osaka University, Japan)
# Toni Moreno (Univ. Rovira i Virgili, ES)
# Hector Munoz-Avila (Lehigh university, Bethlehem, USA)
# Emma Norling (MMU, UK)
# Anton Nijholt (UT, The Netherlands)
# Gregory O'Hare (University College Dublin, Ireland)
# Joost van Oijen (VSTEP, The Netherlands)
# Jeff Orkin (MIT, USA)
# Julian Padget (University of Bath, UK)
# Ana Paiva (IST, Portugal)
# Agostino Poggi (Univ degli Studi di Parma, Italy)
# Colin Price (University of Worcester, UK)
# Michal Pechoucek (CTU, Czech rep.)
# David Pynadath (USC, USA)
# Geber Ramalho (UFPE, Brazil)
# Gopal Ramchurn (University of Southampton, UK)
# Debbie Richards(Macquarie University, Australia)
# Avi Rosenfeld (JCT, Israel)
# Ilias Sakellariou (UOM, GR)
# David Sarne (Bar Ilan University, Israel)
# Maarten Sierhuis (NASA, USA)
# Barry Silverman (UPenn, USA)
# Von-Wun Soo (National Tsing Hua University, Taiwan)
# Pieter Spronck (Tilburg University, The Netherlands)
# Demosthenes Stamatis (TEIHE, GR)
# Ioanna Stamatopoulou (South-East European Research Centre, Thessaloniki, GR)
# Katia Sycara (CMU, USA)
# Duane Szafron (U of Alberta, Canada)
# Rainer Unland (University of Duisburg-Essen, GER)
# Harko Verhagen (Stockholm University/Royal Institute of Technology, SWE)
# Joost Westra (UU, The Netherlands)
# Uri Wilensky (Northwestern University, USA)
# R. Michael Young (North Carolina State University, USA)
Organizers
==========
1 Dr Martin Beer
Communications and Computing Research Centre
ACES
Sheffield Hallam University
Email: m.beer@shu.ac.uk
2 Cyril Brom
Department of Software and Computer Science Education
Faculty of Mathematics and Physics
Charles University in Prague
email: brom@ksvi.mff.cuni.cz
3 Von-Wun Soo,
Department of Computer Science
Institute of Information Systems and Applications
National Tsing Hua University
email:soo@cs.nthu.edu.tw
4 Frank Dignum
Department of Information & Computing Sciences
Utrecht University
The Netherlands
e-mail: dignum@cs.uu.nl
Second CfP for the AAMAS-2011 workshop on
the uses of Agents for Education, Games and Simulations
at the Taipei International Convention Center (TICC) in Taipei, Taiwan on May 2 or 3 2011
In Conjunction with AAMAS 2011
Rationale and technical description
===================================
Training for complex situations in human societies such as in education, business transactions, military operations, medical care and crisis management can be provided effectively using serious games and simulations. In these types of games and simulations the role of agents to model and simulate naturally behaving characters becomes more and more important. Especially in situations where the games are not just meant to provide fun, but are used to support the learning process it is important that the games achieve their goal and do not just distract (or entertain) the trainee.
A major aim of this workshop is to discuss how to model rational (or non-rational, but natural) behaving agents who are embedded in a social context with other characters and humans. This is especially important when both characters and humans can be pro-active but also have to react to the behaviour of others in their environment. Thus these characters should have some social conscience of themselves and others and base their decisions for actions on this knowledge. Of course social knowledge may consist of detailed knowledge such as that some person has been your long time friend and thus can be trusted to help you, but also general knowledge such as that society looks bad at people that cheat but adores people that grasp opportunities. Thus we aim to model also different levels of action and interactions. Both the operational ones such as gestures and general way of animating characters, the tactical decisions such as negotiation tactics when trying to get some help and long term strategies such as behaving cooperative towards your boss in order to secure a promotion. One of the interesting questions is how these should be modelled and how they interact? And how do current agent architectures support these models?
In general the technologies used in game engines and multi-agent platforms are not readily compatible due to some inherent differences of concerns. Where game engines focus on real-time aspects and thus propagate efficiency and central control, multi-agent platforms assume autonomy of the agents. And while the multi agent platforms offer communication facilities these can or should not be used when the agents are coupled to a game. So, although increased autonomy and intelligence may offer benefits for a more compelling game play and may even be necessary for serious games, it is not clear whether current multi agent platforms offer the facilities that are needed to accomplish this.
In this workshop we want to bring people together that address the particular challenges of using agent technology for games and simulations in particular for educational contexts.
The workshop will have four main themes:
1. Technical
What techniques are suitable for agents that are incorporated in educational contexts, games and simulations. How to balance intelligence and efficiency? How to couple the agents to the game/simulation and manage this coupling’s information flow? How to deal with the inherent real time nature of the game engine environment? How to couple long and short time interactions?
2. Conceptual
What information is available for the agents' use, either through the educational context, or from the system, through for example, the game or simulation engine? How can reaction to events be balanced with goal directed behaviour? How are ontological differences between information used by agents and information from the domain handled? How do we choose the actions of an agent? Too high level gives little control; too low level makes the agent inefficient.
3. Design
How do we design interactive systems containing intelligent agents? How do we determine what agents should do and should not do, such that local autonomy and story line are well balanced. How do we design the agents themselves that are embedded in other (possibly diverse) systems (including the behaviour authoring tools and methodologies)?
4. Education
It is also important that we introduce both the design and construction of these collaborative autonomous systems into the computer science curriculum and develop ways of encouraging their effective utilisation across the curriculum. Contributions to the workshop will be welcomed that provide a mixture of relevant theoretical and practical understanding of both the teaching and use of multi-agent systems in educational and entertainment research, together with practical examples of the use of such systems in real application scenarios. These will be written for students, teachers, producers, directors and other professionals who want to improve their understanding of the opportunities offered by the use of multi-agent systems in teaching and entertainment scenarios of all types.
Important Dates
===============
Deadline for receiving papers January 30 2011
Notification to authors February 27, 2011
Camera ready paper March 7, 2011
Workshop May 2 or 3, 2011
Submission Procedure
====================
The workshop welcomes submissions of original works relevant to the topics described above. This year, the workshop will accept submissions of both full papers (maximum 16 pages, LNCS format) and short papers (maximum 8 pages, LNCS format).
Short papers are encouraged as a mechanism for the timely reporting of interesting but preliminary work, that may not as yet have the level of evaluation or detail that would be expected for a regular paper. The program chairs may, at their discretion, accept papers that were submitted as regular papers as short papers, if the authors have explicitly agreed to this when registering their papers.
All accepted regular papers will receive a slot for oral presentation in the conference. The accepted short papers will serve as the basis for discussions during the workshop. If warranted they may be converted to regular papers for the post-proceedings by incorporating the results of these discussions.
Submissions will be peer reviewed rigorously and evaluated on the basis of adherence, originality, soundness, significance, presentation, understanding of the state of the art, and overall quality of their technical contribution. More details about the review process can be found in the conference page.
The papers should be formatted according to LNCS specification and submitted as PDF files. Instructions and templates can be found at
http://www.springer.de/comp/lncs/authors.html.
Final Papers must be submitted on A4 in PDF format. Your paper should not include page numbers.
All final manuscripts should be uploaded to easychair no later than
Sunday 30th January 2011
========================
The submission web site is http://www.easychair.org/conferences/?conf=AEGS-11
Submissions violating the formatting guidelines will be excluded from the reviewing process.
At least one author of all accepted papers is expected to attend the Workshop.
All accepted papers will be informally published in the Workshop proceedings, and the organisers intend to organize a LNCS publication of the workshop proceedings.
PC Committee
============
# Elisabeth Andre (DFKI, Germany)
# Juan Carlos Augusto (University of Ulster, UK)
# Paul Shueh-Min Chang, (National Tsing Hua University, Taiwan)
# Shu-Heng Chen, (National Cheng-Chi University, Taiwan)
# Bill Clancey (NASA, USA)
# Rosaria Conte (ISTC-CNR, Italy)
# Vincent Corruble (LIP6, France)
# Yves Demazeau (CNRS-LIG, Grenoble)
# Virginia Dignum (Technical University Delft, The Netherlands)
# Alexis Drogoul (LIP6, France)
# Bruce Edmonds (MMU, UK)
# Corinna Elsenbroich (University of Surrey, UK)
# Klaus Fischer (DFKI, Germany)
# Rachel E. Goshorn(Naval Postgraduate School, USA)
# Hiromitsu Hattori (Kyoto University, Japan)
# Annerieke Heuvelink (TNO, The Netherlands)
# Dirk Heylen (Univ of Twente, The Netherlands)
# Koen Hindriks (Delft University, The Netherlands)
# Jane Hsu (National Taiwan University, Taiwan)
# Toru Ishida (Kyoto University, Japan)
# Wander Jager (Groningen University, The Netherlands)
# Lewis Johnson (Alelo Inc., USA)
# Gal A. Kaminka (Bar Ilan University, Israel)
# Petros Kefalas (CITY Institute/Sheffield University GR)
# Irving King (Chinese University of Hong Kong, HK)
# Yasuhiko Kitamura (Kwansei Gakuin University)
# Stefan Kopp (University of Bielefeld, Germany)
# Mike van Lent (SOAR technology, USA)
# Michael Lewis (University of Pittsburg, USA)
# MeiYii Lim (Heriot-Watt University, UK)
# Chin-Yew Lin (Microsoft Research Asia, China)
# Shou-De Lin, (National Taiwan University, Taiwan)
# Simon Lynch (Univ. of Teeside, UK)
# Eleni Mangina (Phelan, University College Dublin, Ireland)
# Stacy Marsella, (ISI, Univ of Southern California, USA)
# Michael Mateas, (University of California at Santa Cruz, USA)
# Riichiro Mizoguchi (Osaka University, Japan)
# Toni Moreno (Univ. Rovira i Virgili, ES)
# Hector Munoz-Avila (Lehigh university, Bethlehem, USA)
# Emma Norling (MMU, UK)
# Anton Nijholt (UT, The Netherlands)
# Gregory O'Hare (University College Dublin, Ireland)
# Joost van Oijen (VSTEP, The Netherlands)
# Jeff Orkin (MIT, USA)
# Julian Padget (University of Bath, UK)
# Ana Paiva (IST, Portugal)
# Agostino Poggi (Univ degli Studi di Parma, Italy)
# Colin Price (University of Worcester, UK)
# Michal Pechoucek (CTU, Czech rep.)
# David Pynadath (USC, USA)
# Geber Ramalho (UFPE, Brazil)
# Gopal Ramchurn (University of Southampton, UK)
# Debbie Richards(Macquarie University, Australia)
# Avi Rosenfeld (JCT, Israel)
# Ilias Sakellariou (UOM, GR)
# David Sarne (Bar Ilan University, Israel)
# Maarten Sierhuis (NASA, USA)
# Barry Silverman (UPenn, USA)
# Von-Wun Soo (National Tsing Hua University, Taiwan)
# Pieter Spronck (Tilburg University, The Netherlands)
# Demosthenes Stamatis (TEIHE, GR)
# Ioanna Stamatopoulou (South-East European Research Centre, Thessaloniki, GR)
# Katia Sycara (CMU, USA)
# Duane Szafron (U of Alberta, Canada)
# Rainer Unland (University of Duisburg-Essen, GER)
# Harko Verhagen (Stockholm University/Royal Institute of Technology, SWE)
# Joost Westra (UU, The Netherlands)
# Uri Wilensky (Northwestern University, USA)
# R. Michael Young (North Carolina State University, USA)
Organizers
==========
1 Dr Martin Beer
Communications and Computing Research Centre
ACES
Sheffield Hallam University
Email: m.beer@shu.ac.uk
2 Cyril Brom
Department of Software and Computer Science Education
Faculty of Mathematics and Physics
Charles University in Prague
email: brom@ksvi.mff.cuni.cz
3 Von-Wun Soo,
Department of Computer Science
Institute of Information Systems and Applications
National Tsing Hua University
email:soo@cs.nthu.edu.tw
4 Frank Dignum
Department of Information & Computing Sciences
Utrecht University
The Netherlands
e-mail: dignum@cs.uu.nl
13 Jan 2011
Poster on "Data Integration Models" @ ECCS2011
Edmonds. B. (2010) Data-Integration Models (poster). Eurpean Conference on Complex Systems 2010 (ECCS), Lisbon, September 2010.
Available at: http://cfpm.org/cpmrep211.html
This one the ECCS2010 Best Poster Award.
Available at: http://cfpm.org/cpmrep211.html
This one the ECCS2010 Best Poster Award.
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