At this meeting Milan made a presentation about his research, of which the basic idea is that the agent-based methodology (artificial financial markets), due to its flexibility and bottom-up-approach, are a suitable tool to test the predictions of behavioral finance (a sub discipline that combines financial theories with the insights from psychology and neuroscience in order to give a better description of individual investor behavior).
Milan gave a theoretical background of his research, discussing the components of the conceptual model of individual investor, such as risk attitude, time preference, motivation and goals, strategies, heuristics and biases, emotions, personality, demographics, and dual-process theories of human cognition.
The presentation finished with open questions regarding the actual implementation of the conceptual model.
Tuesday, February 26, 2008
Meeting Minutes - February 14, 2008
During this meeting Milan presented a paper by Jong-Hwan Kim and Chi-Ho Lee: "Multi-objective evolutionary generation process for specific personalities of artificial creature," IEEE Computational Intelligence Magazine (2008).
The summary of the paper is the following:
- Goal: creating a believable artificial creature based on a genome that contains its personality.
- Personalities (the big 5 dimensions) are user-defined by assigning preference values for internal states and behaviors.
- MOEGPP – multi-objective evolutionary algorithm for maintaining the population of genomes.
- Result: the algorithm can create specific (user-defined) as well as diverse (in-between) personalities.
- Verification: the algorithm is verified by checking that the personality characteristics are maintained on a different perception scenario than what is used for optimization.
Some conclusions/questions about the paper are:
- The topic of creating believable artificial creatures was interesting, and seemed like a digression from agent-based papers discussed until now.
- The paper is not self-contained, i.e. it is missing many implementation details (e.g. what is a mask, what are the activation values αk, what is the perception scenario for testing?), some of which are to be found in other cited papers.
- The paper needs more introduction/explanation on why this particular algorithm has been used. Can we do it some other way?
- Jordan wondered whether this algorithm could be used for other OR applications that require multi-objective optimization.
- Uzay asked why the learning module has a direct input from the external environment, rather than through the perception module.
- How can learning be added to these artificial creatures, and how would it be combined with their personalities?
I also found some information about Rity and one video here:
http://rit.kaist.ac.kr/home/Artificial_Creatures_%22Rity%22_and_%22Humanoid%22
http://rit.kaist.ac.kr/~ritlab/research/Artificial_Creatures/rity.wmv
Monday, February 25, 2008
MAS March Madness
Good Morning Everybody,
I just received an invitation to attend a full day workshop on MAS for Production and logistics hosted at the University of Twente. The one catch is that this workshop is on 27 March - the same day Mark Hoogendoorn was supposed to talk to LARGE. So, here are my questions to the group:
1) Who would like to attend the event at the University of Twente?
2) Should we go as a group?
3) When would be a good day to host Mark if we all go to Enschede on the 27th?
Here is the workshop announcement to help you in answering these questions.
I just received an invitation to attend a full day workshop on MAS for Production and logistics hosted at the University of Twente. The one catch is that this workshop is on 27 March - the same day Mark Hoogendoorn was supposed to talk to LARGE. So, here are my questions to the group:
1) Who would like to attend the event at the University of Twente?
2) Should we go as a group?
3) When would be a good day to host Mark if we all go to Enschede on the 27th?
Here is the workshop announcement to help you in answering these questions.
OMPL seminar:
Agent-based control of Production and Logistics: theory, applications, and prospects
March 27, 2008: 10:00-18:00
University of Twente, Enschede
With invited talks by:
Jos van Hillegersberg, University of Twente (NL)
Sunderesh Heragu, University of Louisville (USA)
Han La Poutré, CWI and Technische Universiteit Eindhoven (NL)
In recent years there has been a growing interest in distributed control within the production and logistics domain due to the necessity of greater adaptability and flexibility to changes in the market demand. Agent technology is considered an approach that holds high promises for developing such systems. Multi-agent systems (MAS) are believed to be particularly suited for decentralized systems in real-time and dynamic environments. Because problems are solved locally, these systems should (1) be able to deal with a high level of complexity, (2) require less information exchange than central control methods, (3) respond fast to unexpected events, and (4) reduce system nervousness compared to global optimization. In this seminar we provide a short introduction into agent-theory and present applications of agent-based control of production and logistics.
In the morning we have three invited talks; by Jos van Hillegersberg, Sunderesh Heragu, and Han La Poutré. Peter Schuur will facilitate the discussions. In the afternoon, Martijn Mes will defend his thesis on this topic.
Below we have included the program information. Full abstracts and biographies will be available at our website www.mb.utwente.nl/ompl/agent-seminar. Please register before March, 18th by sending an e-mail to m.r.k.mes@utwente.nl.
Program:
Date: March 27th, 2008, 10:00-18:00
Location: Building Logica (nr 65), University of Twente, Enschede
10:00 – 10:15 Welcome ( Peter Schuur)
10:15 – 10:45 Prof. Dr. Jos van Hillegersberg (University of Twente)
Multi-agent systems: introduction and applications
10:45 – 11:30 Prof. S.S. Heragu (University of Louisville)
Multi-agent systems: warehousing
11:30 – 12:00 Coffee break
12:00 – 12:45 Prof. dr. ir. Han La Poutré (CWI, Technische Universiteit Eindhoven)
Multi-agent systems: transportation
13:00 Lunch
14:45 Introductory talk in Room SP2 (Martijn Mes)
15:00 Public defense in Room SP2 (Martijn Mes)
Sequential Auctions for Full Truckload Allocation
16:30 – 18:00 Drinks and closing
The department OMPL looks forward to seeing you March 27th!
Martijn Mes
Tuesday, February 12, 2008
Meeting Minutes - February 7, 2008
During this meeting Ludo presented Thomas Schelling's spatial proximity model from the book Micromotives and macrobehavior (Norton & Company, 1978), and demonstrated his own applet.
These are some of the questions raised by the participants of the discussion:
- Can we construct a set of individual rules which would lead to a wanted distribution?
- How do we construct complementary rules that lead from segregation to mixing?
- In the model there are only two groups of different preferences. What would happen if some heterogeneity is introduced within the group, e.g. some people are more tolerant of (or even demanding for) people of different kind around?
- What would change if an asynchronous simulation is used? Which implementation choices should be made (e.g. modeling race condition in one thread vs. multiple threads)? Which individual rules would then be used? Would it affect the final result of segregation?
- Are the main findings robust with respect to various implementation choices? For example, there are many ways for choosing dissatisfied people to move (e.g. randomly). According to Schelling these choices do not affect the segregation, but it should be checked in a more thorough way.
This is an interesting page where one can find a link for the implementation of the model in NetLogo (with source code). There is also a link to the extension of the Schelling model by sociologists Burch and Mare, which says (according to abstract) that Schelling’s results are not supported when other (more plausible) preferences are introduced:
http://hsd.soc.cornell.edu/Segregation.htm
This paper by Vinkovic and Kirman examines the shape of the segregated areas using the concept of surface tension force from the physics of liquid:
http://www.pnas.org/cgi/reprint/103/51/19261
These are some of the questions raised by the participants of the discussion:
- Can we construct a set of individual rules which would lead to a wanted distribution?
- How do we construct complementary rules that lead from segregation to mixing?
- In the model there are only two groups of different preferences. What would happen if some heterogeneity is introduced within the group, e.g. some people are more tolerant of (or even demanding for) people of different kind around?
- What would change if an asynchronous simulation is used? Which implementation choices should be made (e.g. modeling race condition in one thread vs. multiple threads)? Which individual rules would then be used? Would it affect the final result of segregation?
- Are the main findings robust with respect to various implementation choices? For example, there are many ways for choosing dissatisfied people to move (e.g. randomly). According to Schelling these choices do not affect the segregation, but it should be checked in a more thorough way.
This is an interesting page where one can find a link for the implementation of the model in NetLogo (with source code). There is also a link to the extension of the Schelling model by sociologists Burch and Mare, which says (according to abstract) that Schelling’s results are not supported when other (more plausible) preferences are introduced:
http://hsd.soc.cornell.edu/Segregation.htm
This paper by Vinkovic and Kirman examines the shape of the segregated areas using the concept of surface tension force from the physics of liquid:
http://www.pnas.org/cgi/reprint/103/51/19261
Saturday, February 2, 2008
New meeting time!
Starting from this week the LARGE group has started to meet weekly on Thursday from 16:00 to 17:00. Please mark you calenders! This generates more opportunities for people to present their research, and the breaks are not that long if there is a holiday in between.
Looking forward to an exciting year with many great LARGE discussions!
- Wolf Ketter
Looking forward to an exciting year with many great LARGE discussions!
- Wolf Ketter
Minutes, January 31, 2008
Today Ruud presented the SugarScape simulation model of Epstein and Axtell.
Ruud briefly discussed the underlying philosophical motivation to the work of Epstein and Axtell. The notion of explanation turns out to be especially important. Epstein and Axtell call their approach generative rather than inductive or deductive, and they regard the generation of a given macrostructure from agent-interaction rules at the micro-level as a necessary condition for explanation of the macrostructure. We did not discuss these philosophical issues in much detail. Instead, we discussed the notion of heterogeneity of agents, which according to Epstein is a characteristic feature of agent-based computational models. This seemed to contradict Wolf's claim from two weeks ago that the heterogeneity of agents in his model is quite unique. We agreed that heterogeneity can exist at two
levels: heterogeneity of an agent's parameter values and heterogeneity of an agent's structure (i.e., the equations/algorithms inside an agent). Although these two kinds of heterogeneity are perhaps not fundamentally different, they may provide an explanation for the apparent contradiction between Wolf's claim and Epstein's paper. We further discussed Epstein's statement that any microspecification that generates a macrostructure of interest is a candidate explanation of that macrostructure. According to Epstein the choice between competing candidate explanations of the same macrostructure should be made by comparing the microspecification of each candidate explanation with the results from laboratory experiments. We doubted whether this is always possible. Uzay and Ruud suggested that a preference for simplicity may be another way to choose between competing candidate explanations. Ruud then showed us some simulations of the SugarScape model.
It was not always immediately clear why certain patterns emerged in the simulations, but at least the patterns usually looked quite intriguing. We realized that for each pattern there may be many different parameters on which the formation of the pattern is crucially dependent. Ruud also showed us simulation examples of something that may be regarded as emergent behavior. Ruud further mentioned that apart from economic research agent-based simulations are also useful in sociological research and perhaps in psychological research. At the end of the meeting the discussion moved from the SugarScape model to the spatial proximity model of Thomas Schelling. However, we decided to devote a separate meeting to the discussion of this model.
-- Ludo Waltman
Ruud briefly discussed the underlying philosophical motivation to the work of Epstein and Axtell. The notion of explanation turns out to be especially important. Epstein and Axtell call their approach generative rather than inductive or deductive, and they regard the generation of a given macrostructure from agent-interaction rules at the micro-level as a necessary condition for explanation of the macrostructure. We did not discuss these philosophical issues in much detail. Instead, we discussed the notion of heterogeneity of agents, which according to Epstein is a characteristic feature of agent-based computational models. This seemed to contradict Wolf's claim from two weeks ago that the heterogeneity of agents in his model is quite unique. We agreed that heterogeneity can exist at two
levels: heterogeneity of an agent's parameter values and heterogeneity of an agent's structure (i.e., the equations/algorithms inside an agent). Although these two kinds of heterogeneity are perhaps not fundamentally different, they may provide an explanation for the apparent contradiction between Wolf's claim and Epstein's paper. We further discussed Epstein's statement that any microspecification that generates a macrostructure of interest is a candidate explanation of that macrostructure. According to Epstein the choice between competing candidate explanations of the same macrostructure should be made by comparing the microspecification of each candidate explanation with the results from laboratory experiments. We doubted whether this is always possible. Uzay and Ruud suggested that a preference for simplicity may be another way to choose between competing candidate explanations. Ruud then showed us some simulations of the SugarScape model.
It was not always immediately clear why certain patterns emerged in the simulations, but at least the patterns usually looked quite intriguing. We realized that for each pattern there may be many different parameters on which the formation of the pattern is crucially dependent. Ruud also showed us simulation examples of something that may be regarded as emergent behavior. Ruud further mentioned that apart from economic research agent-based simulations are also useful in sociological research and perhaps in psychological research. At the end of the meeting the discussion moved from the SugarScape model to the spatial proximity model of Thomas Schelling. However, we decided to devote a separate meeting to the discussion of this model.
-- Ludo Waltman
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