UTCS Colloquium/AI-Matthew Taylor/University of Southern California: "Balancing Multi-agent Exploration and Exploitation in Time-Critical Domains" TAY 3.128 Friday, May 29, 2009 11:00 a.m.
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Talk: UTCS Colloquium/AI
Taylor/University of Southern California
May 29, 2009 11:00 a.m.
Location: TAY 3.128
: Peter Stone
Talk Title: "Balancing Multi-agent
Exploration and Exploitation in Time-Critical Domains"
Substantial work has investigated balancing exploration and exp
loitation, but relatively little has addressed this trade-off in the conte
xt of coordinated multi-agent interactions. In this talk I will introduce a
class of problems in which agents must maximize their on-line reward, a d
ecomposable function dependent on pairs of agents decisions. Unlike previou
s work, agents must both learn the reward function and exploit it on-line
, critical properties for a class of physically motivated systems, such as
mobile wireless networks. I will introduce algorithms motivated by the Dis
tributed Constraint Optimization Problem framework and demonstrate when, a
nd at what cost, increasing agents coordination can improve the global rew
ard on such problems.
I will also briefly discuss a couple of ad
ditional projects I have worked on at USC in the past two semesters.
Matthew E. Taylor is a postdoctoral research associate a
t the University of Southern California working under Milind Tambe. He grad
uated magna cum laude with a double major in computer science and physics f
rom Amherst College in 2001. After working for two years as a software deve
loper, he began his Ph.D. with a MCD fellowship from the College of Natura
l Sciences. He received his doctorate from the Department of Computer Scien
ces at the University of Texas at Austin in the summer of 2008. Current res
earch interests include multi-agent systems, reinforcement learning, and
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