CS Colloq: Synthesis of Strategies for Noisy and Non-Noisy Multi-Agent Environments

Title: Synthesis of Strategies for Noisy and Non-Noisy Multi-Agent EnvironmentsSpeaker: Tsz-Chiu Au (UMD)ABSTRACT:
To create new and better agents in multi-agent environments, we may want to
examine the strategies of several existing agents, in order to combine their
best skills. One problem is that in general, we won¡¦t know what those
strategies are; instead, we¡¦ll only have observations of the agents¡¦
interactions with other agents. In this talk, I describe how to take a set of
interaction traces produced by different pairs of players in a two-player
repeated game, and then find the best way to combine them into a composite
strategy. I also describe how to incorporate the composite strategy into an
existing agent, as an enhancement of the agent¡¦s original strategy. In
cross-validated experiments involving 126 agents (most of which written by
students as class projects) for the Iterated Prisoner¡¦s Dilemma, Iterated
Chicken Game, and Iterated Battle of the Sexes, composite strategies produced
from these agents were able to make improvement to the performance of nearly
all of the agents.The speaker will also talk about a technique, Symbolic Noise Detection (SND),
for detecting noise (i.e., mistakes or miscommunications) among agents in
repeated games. The idea behind SND is that if we can build a model of the
other agent's behavior, we can use this model to detect and correct actions
that have been affected by noise. In the 20th Anniversary Iterated Prisoner's
Dilemma competition, the SND agent placed third in the ¡§noise¡¨ category, and
was the best performer among programs that had no ¡§slave¡¨ programs feeding
points to them. I'll discuss how to combine SND with the strategy synthesis
technique in order to produce agents that perform well in noisy, cooperative
environments.BIO:
Tsz Chiu Au is a graduate student at Dept. at Comp. Sci, Univ. of Maryland.
(expected PhD in 2008). He received his B. Eng. degree from Hong Kong Univ. of
Science and Technology.
His research interests lie in AI planning, multi-agent systems and problem
solving by searching. His research accomplishments include his work on coping
with noise in non zero-sum games, synthesis of strategies from interaction
traces and managing volatile data for planning processes in semantic web
service composition.

Location: Seaver Science Library (SSL) - 150

Audiences: Everyone Is Invited

Contact: CS Colloquia