Learning to cooperate in normal form games

Steven Damer, Maria L Gini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

We study the problem of achieving cooperation between two self-interested agents that play a sequence of randomly generated normal form games, each game played only once. To achieve cooperation we extend a model used to explain cooperative behavior by humans. We show how a modification of a pre-regularized particle filter can be used to detect the cooperation level of the opponent and play accordingly. We examine how properties of the games affect the ability of an agent to detect cooperation and explore the effects of different environments and different levels of conflict. We present results obtained in simulation on hundreds of randomly generated games.

Original languageEnglish (US)
Title of host publicationInteractive Decision Theory and Game Theory - Papers from the 2010 AAAI Workshop, Technical Report
Pages2-9
Number of pages8
StatePublished - Dec 1 2010
Event2010 AAAI Workshop - Atlanta, GA, United States
Duration: Jul 12 2010Jul 12 2010

Publication series

NameAAAI Workshop - Technical Report
VolumeWS-10-03

Conference

Conference2010 AAAI Workshop
Country/TerritoryUnited States
CityAtlanta, GA
Period7/12/107/12/10

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