Meeting Minutes - 18 December 2008

Today, I (Meditya Wasesa)have presented a working paper entitled "Time is money: The Effect of Clock Speed on Seller's Revenue in Dutch Auction" written by Elena Katok and Anthony M. Kwasnica of Department of Economics of Smeal College of Business, Penn State University.

The paper presents an experiment and a formula that show the correlation between the clock speed and the sellers revenue in dutch auction. In brief, slower clock speed brings lower revenue, and faster clock speed brigs higher revenue. They have built a nice simple formula that explains this phenomenon by the use of the monitoring cost and the non monetary enjoyment, as the time affected parameters as important factors that affect the end revenue.


In the discussion, the group discussed troughly about the experiment settings that this paper utilized. We tried to analized the pros and the cons about the settings and the formulation which we want to extend at our proposed dutch flower auction experiment.

Meeting Minutes - 3 December 2008

Today, I (Meditya Wasesa) have presented a working paper entitled “A Structural Empirical Analysis of Dutch Flower Auction” written by Gerard van der Berg and Bas van der Klaauw of Department of Economics of Free University Amsterdam.

The paper goals are to define the bidders valuation, determine the optimal seller's reserve value, and see the effect of reserve value adjustment (changing the value of current reserve value to the calculated reserve value) to the corresponding revenue. It is presumed that by adjusting the existing reserve value to an optimized value, a higher revenue could be gained.

The one that is interesting, the authors did not only observed the winning bids record, but also the losing bids (in an interval up to 1 second). Similar previous papers usually only consider the winning bids in their model. They believe that this extra observation could improve their prediction on the distribution of private values of the bidders. The other thing that the writers did is that they use a markov chain monte-carlo and gibbs sampling in the projection of the private values of the bidder.

In general, the flow of the research can be presented as the scheme above. First they observe the recorded data (winning and losing bids). Second they try to mimic the historical data to a valuation distribution of bidders by using the a markov chain monte-carlo and gibbs sampling (they do this step in 4 scenarios). Third then they calculate the optimal reserve bid and also the corresponding delta of revenue. By their finding the increment of the reserve price will not bring big change to the increase of the revenue.

However the conclusion of this paper is not final yet, the team planned to have another discussion about this paper in some other time to really grasp the essence of the paper.

Meeting Minutes – 26 November 2008

Today, Paul R. Schrater a guest researcher from University Minnesota, has made a presentation about active preference learning topics. He explained a topic of probability model in which an agent can derive a continous valuation formula which is a result from learning algorithm from a set of discrete data. He tried to explained the algorithm which can decide what approximate formula can be presented to an individual in order to find the projected result that they value highly in as few trial as possible, without making an accurate model the entire valuation surface.



About the presenter,

Paul R. Schrater hold a joint faculty position at the University of Minnesota, in the departments of Psychology and Computer Science. His current research interests generally involve using probabilistic methods to study issues in perception and motor control. He received his Ph.D. from the Department of Neuroscience of the University of Pennsylvania, under David Knill, then of the Department of Psychology and Eero Simoncelli in the GRASP Laboratory who at that time had a primary appointment in the Department of Computer Science at Penn. His dissertation involved a psychophysical and ideal observer analysis of local motion processing.

Meeting Minutes - 19 November 2008

Today, the LARGE session has had a very nice presentation from Carsten Block, a ready to finish doctoral candidate of Information & Market Engineering department, TU Karlsruhe Germany. At our session he presented the topic of "Market-Based Control and Agent-Based Trading in Combined and Power Grids." which is pretty much the topic which has been the area of his doctoral specialization.

The background of the research is the emerging trends of the energy supply which is no longer in hierarchical setup of up down (e.g. from the source to household) distribution, but also in the reversal direction. So that not only the source can sell their energy to the downstream but also the downstream line if they produce energy, the downstream costumer can also sell their energy to the upstream.

This issue of developing two ways of distribution is explained pretty much from different perspectives. But especially, since the energy transaction mechanism between the upstream and the downstream mechanism is built in the agent based point of view and also the mechanism of transaction is involving auction mechanism, so a lot of things what Carsten have applied in his research pretty much coherent with the LARGE field. This session off course has brought big lesson fur the group.

The discussion of this reversible energy transaction is pretty much done in multiple perspectives, since in this session a lot of people come from different area of specialization (e.g. economics, business network, information and decision sciences, etc). Carsten did an excellent explanation also to the multi-background viewer’s questions.

Since Carsten have a strong computer science background, he also shared some of his experiences (e.g. tool for development) in the development of his project. He introduced us a new tools for faster software development like grailsTM and make some demo also about what the platform advances. This session was very successful and everybody was enthusiastic.

Meeting Minutes - 12 November 2008

Today Uzay Kaymak gave a presentation on the Ming Hua and Nicholas Jenning's paper of "Designing a Successful Trading Agent: A Fuzzy Set Aproach".

The paper tells us about the writers experience in implementing fuzzy logics in their SouthamptonTAC agent.

SouthhamptonTAC agent participated successfully in the first and second (TAC) Trading Agent Competition, a competition which facilitates the competition of the participant's "travel" agents in fulfilling their customer demand of travel package (flight ticket, hotel, and extra entertainment ticket). Those participating agents should compete with each other in different (flight ticket, hotel, and extra entertainment ticket) auctions provided by the TAC platform to statisfy the demand of the agent's costumer.

Uzay briefly explains how the SouthamptonTAC implements the fuzzy logics in the hotel, ticket, and entertaiment bidding actions. He (Uzay) found it quiet surprising how the performance of the fuzzy rules implementation can work well on the competition.

The presentation, is wrapped up by a small discussion about the competition conditions. Wolf gives the audience some description about the condition of the TAC competition (The rounds, the finalists, etc.).

Meeting Minutes - 15 October 2008

Katalin led a discussion on the agent definitions and agent properties. She presented first a number of definitions from the literature mainly based on the article by Franklin and Gaesser. We compared and analyzed these definitions, especially w.r.t. to their properties and also discussed how these relate to the broad definition by Norvig and Russel.

It seems that there are three types of agents defined: “agents”, “autonomous agents” and “intelligent agents”. It is not always clear, however whether authors mean in fact agents with different properties when using these notions. Autonomy is a basic property that seemingly all agents should possess. However, we couldn’t really agree on what autonomy means. Explanations we gave varied from the notion of being “independent” to being “goal-oriented”, “pro-active”. The conclusion is that there are different degrees of autonomy.

With respect to the agents properties it also seems that learning and adaptation are sometimes interchanged.

In the second part of the meeting the CAS (Complex Adaptive System) definition has been focused, and agent-based modeling as an approach. Here the focus is on agents as interactive individual entities, and the emergent system properties. Agents are classified in three classes based on the rules they use and their level of adaptation: simple agents, complex-rule agents and advanced-rule agents.

Katalin concludes that we shouldn’t really bother about the many definitions; there are agents with different properties and different complexities. What should be important, however, is that authors give a clear description of what they call an “agent” in their paper, which properties the agents have, with definition of these properties.

Meeting Minutes - 21 July, 2008

Today Peter Berends held a presentation discussing the case “The Application of Intelligent Personalised Agents for Buyer Decision Empowerment at the Dutch Flower Auction (DFA)”.

The DFA consists of six individual auctions located throughout the Netherlands which each host a couple of clock auctions on which goods are auctioned. In total there are 39 clocks on the DFA.

When buying through a clock auction, buyers aim to buy at the lowest price. Thus, they try to show their interest at the very latest possible moment. However, caution needs to be exercised because reacting too late means forgoing the ability to buy the auctioned product because other buyers might have jumped on the opportunity. As a consequence, buying through clock auctions is not an easy job. There is also a remote application through which buyers can buy at the DFA from any location. Many buyers procure for their customers who are located at different locations, and there are six different auctions of the DFA in the Netherlands. This means that when remotely buying, buyers could optimise the transportation cost and transportation time by making sure they buy products from an auction that is in close proximity to the location where they need to ship the goods.

This means that there are four main decision parameters to be considered with every buy: (1) price; (2) quality measures; (3) transportation costs; and (4) transportation time. There was a discussion on how intelligent agent-based systems could be utilized to empower buyers in their decision making.

After the presentation a discussion was held about where best to apply the agents, their benefits, and the information the agents need to base its decision on.

Meeting Minutes - 23 June, 2008

Today Wolf gave a presentation on the ICEC '08 paper "A Semantic Web Architecture for Advocate Agents to Determine Preferences and Facilitate Decision Making". The paper deals with the architecture of a new kind of autonomous agents.

The main motivation of applying these personalized agents is that they can complement the cognitive limitations of the human mind, and therefore facilitate the decision making process to, reduce information overload (bounded rationality), increase work efficiency (i.e. speed up real-time managerial decisions), increase productivity (cost savings and ROI), increase solution (product or service) quality. Besides these tangible benefits, there are also intangible benefits, e.g. greater customer and employee satisfaction. In order to do this, these agents need to work effectively and efficiently with the human user. Meaning that the agent must learn the human user's interests, habits and preferences (as well as those of their communities). In an online retail example, recommendations can be given as to what to buy (product-brokering) and from whom to buy (merchant-brokering), based on customer criteria.

Agents and the human work in a bi-directional way through the interface called: Economic Dashboard.
"You cannot manage what you do not measure"
"What gets watched, gets done."

These statement demonstrate what the Economic Dashboard is, an "Organizational Magnifying Glass" – to focus the work of employees so everyone is going in the same direction! It business people: (1) Monitor, (2) Analyze, (3) Manage, (4) and Communicate and give feedback to the agent.

In order to work with the Economic Dashboard at all of the different organizational levels, these Economic dashboard has three types that relate to Business Intelligence:
Strategic BI: Achieve long-term organizational goals
Tactical BI: Conduct short-term analysis to achieve strategic goals
Operational BI: Provide a decision-making environment that reduces the latency between the time a significant business event happens and the business' ability to react to it.

In order to bring these personalized results, and work with the personalized results in the Economic Dashboard preferences are elicitated. Preference elicitations is the central concept of decision making and is fundamental for the analysis of human choice behavior, since people have different preferences for different roles. There are four methods or preference elicitation: (1) Questionnaire, which define roles, areas, objectives, and tasks; (2) Implicit feedback through user observation through browser extension (Piggy Bank, etc.), (3) Explicit user feedback through economic dashboard, and none intrusive sidebar in browser window, and (4) Business and Social Networks (Professional (intra company e.g. IBM, Linkedin, Plaxo, etc.) Personal (Facebook, Hi5, Hyves, etc.).

These preferences are saved in RDF stores, which allows the best abilities to apply Semantic Web agents.

In conclusion, this paper demonstrates the feasibility of Advocate Agents by presenting an architecture that integrates current technologies, such as Enterprise Service bus, XML, RDF, and machine learning techniques into a unique system and demonstrating that all the components of Advocate Agents can be built from already existing methods and elements.

After the presentation a discussion was held.

Next LARGE meeting is scheduled for 21 July.

Meeting Minutes - 16 June, 2008

Elfriede Krauth presented a paper (together with Wolf Ketter and Jacqueline Bloemhof ) on Business Intelligence: Academic vs. Industry Perspective. Dashboards are distinguishing features between the disciplines.

Meeting Minutes - 9 June 2008

Today, Ludo presented his research under the title ‘An Algorithm for Calculating the Long-Run Behavior of Genetic Algorithms in Economic Modeling’. Ludo first gave a brief overview of the research topic with which he is concerned. This is the topic of economic modeling using genetic algorithms. Ludo then discussed, at an informal level, the theoretical results that he has obtained. From these results, an algorithm can be derived that makes it possible to calculate the long-run behavior of genetic algorithms in economic modeling. Finally, Ludo discussed the application of this algorithm to a frequently cited study by Robert Axelrod (1987) on genetic algorithm modeling in iterated prisoner’s dilemmas.

Meeting Minutes - 2 June 2008

Today, 2 June, Jordan presented a summary of three presentations given at the OMPL seminar on Agent-based control of Production and Logistics: theory applications and prospects. This seminar was originally hosted on 27 March at the university of Twente. Jordan provided an overview of the presentations given by Prof. Heragu and Prof. La Poutre as well as a summary of the MAS/"OR heuristics" comparison performed by Martijn Mes.

Meeting Minutes - May 26, 2008

Today, Ludo presented the paper Robust Evolutionary Algorithm Design for Socio-Economic Simulation by Floortje Alkemade, Han La Poutré, and Hans Amman (Computational Economics, 28(4), 355–370, 2006). After a brief overview of the paper, the discussion focused on the main reasoning followed by the authors. Some objections against this reasoning were raised. We also discussed an error in the paper, focusing on what we can learn from the error and how such errors can be avoided as much as possible.

Meeting Minutes - 14 April, 2008

During this meeting Katalin has summarized a working paper on a taxonomy proposed for artificial stock markets (ASMs). The taxonomy is aimed to give a guideline for analyzing, comparing, replicating and designing ASMs. The main factors proposed are extracted from the market microstructure literature, and representation aspects are added based on the literature on ASMs. Two main groups of factors are distinguished that are used to describe real and artificial stock markets: organizational aspects and behavioral aspects. The first group is related to market organization and it contains static, well-defined aspects, such as: the type of stocks, orders, participants, trading sessions, and exchange mechanism. The second group is related to the hardly observable and varying aspects of markets such as price formation and the behavior of the various market participants. An overview of 15 various ASMs has been given using the taxonomy. The variety of various trading strategies implemented within ASMs has been illustrated. An interesting discussion point is whether and to what degree are the represented traders in these ASMs "agents", and to what degree are they "autonomous".

Meeting Minutes - March 6, 2008

During this meeting Ludo presented the paper Evolutionary Games and Spatial Chaos by Martin Nowak and Robert May (Nature, 359, 826-829, 1992). The authors introduce a simple evolutionary model for the emergence of cooperative behavior in prisoner’s dilemmas. Unlike previous models, the model introduced by the authors does not rely on reciprocity to explain cooperative behavior. Instead, the model assumes that agents are located on a two-dimensional grid and interact only with their neighbors. Evolution also takes place locally. It turns out that under these assumptions cooperative behavior can emerge for certain values of the prisoner’s dilemma payoffs. The contribution of the paper is that it provides the important insight that apart from reciprocity the spatial distribution of agents can help to sustain collusion. At the time the paper was published this was a new insight. The results of Nowak and May have been confirmed and generalized in a large number of studies. In addition to biologists, some economists have also been inspired by Nowak and May’s paper and have studied the implications in economic contexts.

Meeting Minutes - February 21, 2008

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.

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

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.

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

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

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

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