Evaluating the minority game strategy in agent role assignments

Tingting Wang*, Jiming LIU

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

A team-based competitive environment is a complex multiagent environment, in which agents are required to coordinate with each other not only to enhance their collective behavior, but also to compete with the other team. An interesting research problem in such an environment is the role assignment problem (RAP). The problem requires agents to decide the roles they should take based on real-time feedback from a dynamically changing environment. In this paper, we aim to provide a new strategy that is based on the Minority Game (MG) model, i.e., the MG strategy, for assisting a team to perform effective role assignments in such an environment. Through experiments in our previous work, we have demonstrated that the MG strategy is helpful for RAP in RoboCup Simulation League. In this paper, with a more generic competitive environment such as DynaGrid, we find that the MG strategy is not always effective. It can help agents do effective roles assignments in the case that the targets move in a nonlinear motion.

Original languageEnglish
Pages1417-1418
Number of pages2
Publication statusPublished - 2005
Event4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05 - Utrecht, Netherlands
Duration: 25 Jul 200529 Jul 2005

Conference

Conference4th International Conference on Autonomous Agents and Multi agent Systems, AAMAS 05
Country/TerritoryNetherlands
CityUtrecht
Period25/07/0529/07/05

Scopus Subject Areas

  • Engineering(all)

User-Defined Keywords

  • Competition
  • Multi-agent
  • Role assignment
  • Teamwork

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