Discussion Topics

I'm interesting to continue the discussion of preference modeling, and maybe extending into the area of complexity economics, but I'm also open to new topics and suggestions. Please tell me what are you suggestions? Thanks, Wolf

CfP - TADA 2008

Call for Papers for the 2008 Trading Agent Design and Analysis workshop. Note that the 14 July date is not yet completely certain - it may be one day earlier on 13 July, but we hope to nail that down very soon. Watch the website for updates: http://tac.cs.umn.edu/tada08

We hope to see you in Chicago next year!

Wolf Ketter, RSM Erasmus University

Alex Rogers, Southampton University

Norman Sadeh, Carnegie Mellon University

William Walsh, CombineNet

MAS course + article library

The multi-agent systems research workshop at RSM will be held on January 21-23 and on March 10-11. A tentative schedule is available now. This can also serve as a start for categorized agent library for LARGE which we update each time we discuss new articles. It can also serve as a basis for discussion in the light of our next meeting on Dec 6th where Uzay will finish presenting the last paper and then we'll think about the future topics. Enjoy the articles! If you have questions please contact me. Wolf

Collection of PCA sites

Production Differentitation PCA:
http://pricescan.com/ -- often biased to one brand in one particular category

Product Evaluation PCA:
http://www.bizrate.com/

Consumer Preference Identification PCA:
http://www.epinions.com/

Derivative PCA:

www.bestbuyfinder.com
http://dealtime.com/
http://www.shopping.com -- (rebranded from dealtime.com) close-coupled agent design that integrates different PCAs into its architecture -- while you start searching it gives you product suggestions, an advocate agent would give you products related to your preferences since it got to know you over time

An aggregate of the 3 main PCAs with social tagging and customer reviews
http://www.pronto.com/

Refine as you type comparison shopping agents:

http://www.smarter.com/
http://www.become.com/

Meeting minutes November 8, 2007

We had a discussion on the paper "E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact" by Bo Xiao and Izak Benbasat that appeared in MIS Quarterly, Vol. 31, No. 1, pp.137-209 (2007). Here are some of the discussion questions and remarks.

• Can we use the findings of this paper to apply RAs in B2B environments, in particular in supply chains, or in another domain fit to our interests?
• Can we use the findings of this paper to come up with general design principles of such RAs?
• Do we appreciate the methodology of this paper, do we understand it? Do we need to?
• Do we want to study this paper and (some of) its references in more detail, and what will be our objectives?
• How would (virtual) social networks moderate the impact of and trust in RAs on consumer decision making; should we introduce the concept of multi-RA systems? What are requirements on the (virtual) social network here?
• Important characteristic of an RA is the use of a model of user behavior (similarity). In this sense, descriptive theory on e.g. behavior of actors in financial markets may be a first step towards the design of RAs in that context.
  

Meeting Minutes - 25 October 2007

In the LARGE meeting on 25 October, Jordan gave a dry run of her presentation for the upcoming INFORMS meeting. The presentation was entitle How "Good" are Multi-Agent Systems for the Dynamic Vehicle Routing Problem? Jordan began the presentation by defining the terms in the title, then motivated the topic by a review of the literature, described the methodology of her comparative analysis, and concluded with the results of the analysis.

Overall, the results indicate that multi-agent systems have the capacity to perform competitively in highly dynamic settings. The presentation as a whole could benefit by spending more time on the problem specification, definition of terms, and details of the methodology. Jordan acknowledged these comments and is presently working to add more graphics to the presentation to facilitate defining all the technical terms.

Following Jordan's presentation a brief discussion of the paper, Designing a Better Shopbot, by Montgomery, Hasanagar, Krishnan, and Clay, was held. In this discussion it was generally felt that:
1) The theory was interesting and the detailed description of the shopbot algorithm was computationally intriguing. However, the approached missed out on the psychology of on-line shopping. Thus, the usefulness of such a shopbot was called into question.
2) The product under analysis in this paper is books. As a result, the real power of the algorithm was never truly challenged. That is, the power of the algorithm lies in an ability to track and forecast prices in order to make 'intelligent' suggestions of books to purchase. Unfortunately, book prices do not fluctuate significantly; it would therefore be particularly interesting to apply this model to products with moe price variation - i.e. travel.
3) It was further noted that books do not have too many attributes. So again products, like travel or cell phones, with many many attributes would be a more interesting test of the agent framework.

The meeting concluded with a particularly brief mention of the big paper for next meeting's discussion - E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact by Xiao and Benbasat. Ruud mentioned that he liked what he saw in this article because it seemed that the newer generation of shopping agents described therein incorporated more elements of behavioural decision making theory.

Finally, Wolf announced that the next meeting, 8 November 2007, would focus on the Xiao and Benbasat paper including a presentation by Rob Zuidwijk.

Welcome to the LARGE Blog

The LARGE (Learning Agent Research Group at Erasmus) blog is a place where our team of researches can discuss all aspects of multi-agent systems and machine learning applied to business and economic environments.

Our homepage at the Rotterdam School of Management (RSM) at Erasmus University:

http://large.rsm.nl

If you want to participate in LARGE please email Wolf Ketter (wketter@rsm.nl).

- Wolf