AIC Seminar Series
Measuring Information Transmission for Team Decision Making
| Timothy W. Rauenbusch | Harvard University | |
Date: Thursday June 24, 2004 at 16:00
Location: EJ228 (Directions)
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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.
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Bio for Timothy W. Rauenbusch |
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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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