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.
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