Synthesis of strategies from interaction traces

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

We describe how to take a set of interaction traces produced by different pairs of players in a two-player repeated game, and combine them into a composite strategy. We provide an algorithm that, in polynomial time, can generate the best such composite strategy. We describe how to incorporate the composite strategy into an existing agent, as an enhancement of the agent's original strategy. We provide experimental results using interaction traces from 126 agents (most of them written by students as class projects) for the Iterated Prisoner's Dilemma, Iterated Chicken Game, and Iterated Battle of the Sexes. We compared each agent with the enhanced version of that agent produced by our algorithm. The enhancements improved the agents' scores by about 5% in the IPD, 11% in the ICG, and 26% in the IBS, and improved their rank by about 12% in the IPD, 38% in the ICG, and 33% in the IBS.

Original languageEnglish
Title of host publication7th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2008
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages837-844
Number of pages8
ISBN (Print)9781605604701
StatePublished - 2008
Event7th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2008 - Estoril, Portugal
Duration: 12 May 200816 May 2008

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference7th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2008
Country/TerritoryPortugal
CityEstoril
Period12/05/0816/05/08

Funding

FundersFunder number
Air Force Office of Scientific ResearchFA95500610295, FA95500510298, FA95500610405
National Science FoundationIIS0412812, IIS0705587

    Keywords

    • Agents
    • Interaction
    • Learning
    • Multi-agent systems
    • Prisoner's dilemma
    • Repeated games

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