Minority game strategies in dynamic multi-agent role assignment

Tingting Wang*, Jiming LIU, Xiaolong Jin

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

In a team-based competitive game, agents cooperate to enhance their collective performance in winning the game. An interesting research problem in a team-based game is the role assignment problem (RAP). The problem requires agents to decide their respective roles based on real-time feedback from a dynamically changing environment. The Minority Game (MG), as used in modeling financial marketing problems, has shown similar characteristics that meet the fundamental requirements of RAP. In this paper, we propose a formulation of MG strategies for studying RAP in a specific team-based game: RoboCup Simulation League (RSL). Through experimentation, we demonstrate that MG strategies improve the effectiveness of role assignment among agents. The improvement validates some characteristics, e.g., the phase transition phenomenon on the memory size, as discovered in the theoretical MG model.

Original languageEnglish
Title of host publicationProceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Systems. IAT 2004
EditorsN. Zhong, J. Bradshaw, S.K. Pal, D. Talia, J. Liu, N. Cercone
Pages316-322
Number of pages7
Publication statusPublished - 2004
EventProceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004 - Beijing, China
Duration: 20 Sep 200424 Sep 2004

Publication series

NameProceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004

Conference

ConferenceProceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004
Country/TerritoryChina
CityBeijing
Period20/09/0424/09/04

Scopus Subject Areas

  • Engineering(all)

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