Carnegie Mellon SCS DISTINGUISHED LECTURE: Thurs/September 18

[Dave Farber <dave () farber net>]

> SCHOOL OF COMPUTER SCIENCE DISTINGUISHED LECTURE
> ------------------------------------------------
> Thursday, 18 September 2003
> Wean Hall 7500
> 3:45 pm - Distinguished Donuts
> 4:00 pm - Lecture
>
>
>
>      TUOMAS SANDHOLM
>      ----------------
>      Associate Professor of Computer Science
>      Director, Agent-Mediated Electronic Marketplaces Lab
>      Carnegie Mellon University
>
>
>         MAKING MARKETS AND DEMOCRACY WORK:
>          A STORY OF INCENTIVES AND COMPUTING
>
>
>          This talk is a representation of Dr. Sandholm's
>          IJCAI "Computers and Thought Award" Lecture 2003.
>
>
> ABSTRACT
> ********
> Collective choice settings are the heart of society. Game theory
> provides a basis for engineering the incentives into the
> interaction mechanism (e.g., rules of an election or auction) so
> that a desirable system-wide outcome (e.g., president, resource
> allocation, or task allocation) is chosen even though every agent
> acts based on self-interest.
>
> However, there are a host of computer science issues not
> traditionally addressed in game theory that have to be addressed
> in order to make mechanisms work in the real world. Those computing,
> communication, and privacy issues are deeply intertwined with the
> economic incentive issues. For example, the fact that agents have
> limited computational capabilities to determine their own (and others')
> preferences ruins the incentive properties of established auction
> mechanisms, and gives rise to new issues. On the positive side,
> computational complexity can be used as a barrier to strategic
> behavior in settings where economic mechanism design falls short.
>
> Novel computational approaches also enable new economic institutions.
> For example, market clearing technology with specialized search
> algorithms is enabling a form of interaction that I call expressive
> competition. As another example, selective incremental preference
> elicitation can determine the optimal outcome while requiring the
> agents to determine and reveal only a small portion of their
> preferences. Furthermore, automated mechanism design can yield
> better mechanisms than the best known to date.
>
>
> SPEAKER BIO
> ***********
> TUOMAS SANDHOLM is an associate professor in the Computer Science
> Department at Carnegie Mellon University.  He received the Ph.D.
> and M.S. degrees in computer science from the University of
> Massachusetts at Amherst in 1996 and 1994.  He earned an M.S.
> (B.S. included) with distinction in Industrial Engineering and
> Management Science from the Helsinki University of Technology,
> Finland, in 1991.  He has published over 160 technical papers on
> artificial intelligence; electronic commerce; game theory; multiagent
> systems; auctions and exchanges; automated negotiation and contracting;
> coalition formation; voting; safe exchange; normative models of bounded
> rationality; resource-bounded reasoning; machine learning; networks; and
> combinatorial optimization.
>
> Dr. Sandholm has 13 years of experience building electronic
> marketplaces, and several of his systems have been commercially
> fielded.  He is also Founder, Chairman, and Chief Technology Officer
> of CombineNet, Inc.  He received the National Science Foundation
> Career Award in 1997, the inaugural ACM Autonomous Agents Research
> Award in 2001, the Alfred P. Sloan Foundation Fellowship in 2003,
> and the IJCAI Computers and Thought Award in 2003.
>
>
>                         ************************

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