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AIC Seminar Series

Measuring Information Transmission for Team Decision Making

Timothy W. RauenbuschHarvard University

Date:  Thursday, June 24th 2004 at 4:00pm

Location:  EJ228  (Directions)


A fundamental problem in designing multiagent systems is to select algorithms that make correct group decisions effectively. Typically, each individual in a group has private, relevant information and making a correct group decision requires that private information be communicated. When there is limited communication bandwidth or potential for delays in communication, it is important to select the algorithm for making group decisions that requires least communication. In this talk, I will describe the benefits of quantifying information transmitted by measuring the entropy of messages to find algorithms for decision making that minimize use of bandwidth. I will show the results of the analysis of information content of a diverse group of center-based algorithms, including several types of auctions, for making group decisions. I will present a new data structure, the dialogue tree, that compactly represents complex interactions between individuals and show how it is used to measure the information transmitted by an algorithm. The talk will demonstrate that the amount of communication required by an algorithm is highly dependent on factors of the multiagent system's environment, such as team size, error tolerance, and the likelihood that a given agent can perform a particular task. No single algorithm guarantees the least communication in all environments. A system designer must consider both coordination and revelation when choosing an algorithm. I show that systems that implement an unsuitable algorithm for decision making incur significant costs for wasted communication.

   Bio for Timothy W. Rauenbusch

Timothy Rauenbusch received his Ph.D. in Computer Science from Harvard University in June 2004. His thesis was entitled Measuring Information Transmission for Team Decision Making. His research has focused on the development and analysis of algorithms for team decision making. He has also worked to develop computer systems that support negotiation among people. Tim received his undergraduate degrees in Finance and Computer Science (Summa cum Laude) from the University of Pennsylvania in 1996. At Penn, he received the General Alumni Society’s Student Award of Merit in part for writing the Quick Start Manual for Eniac, the world’s first general-purpose digital computer. Before returning to research, Tim worked on Wall Street as an investment banker. Tim was a visitor at SRI during academic year 2001-2002.

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