Two-sided parameter learning of role selections for efficient team formation

Dai Hamada, Toshiharu Sugawara

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

1 Citation (Scopus)


We propose a method of learning to determine appropriate roles for forming efficiently teams by self-interested agents in task-oriented domains. Service requests on computer networks have recently been rapidly increasing. To improve the performance of such systems, issues with efficient team formation to do tasks have attracted our interest. The main feature of the proposed method is learning from two-sided viewpoints, i.e., team leaders who have the initiative to form teams or team members who work in one of the teams that are solicited. For this purpose, we introduce three parameters to agents so that they can select their roles of being a leader or a member. Then, an agent can anticipate what other agents should be selected as team members and what team it should join. Our experiments demonstrated that the amount of utility earned as the result of successful team formation was considerably larger than that with a conventional method. We also conducted a number of experiments to investigate the characteristics of the proposed method. The results revealed that the divisional cooperation between agents was developed, which could reduce the chance of conflicts in decisions to play roles and this achieved efficient team formation.

Original languageEnglish
Title of host publicationPRIMA 2012
Subtitle of host publicationPrinciples and Practice of Multi-Agent Systems - 15th International Conference, Proceedings
PublisherSpringer Verlag
Number of pages15
ISBN (Print)9783642327285
Publication statusPublished - 2012
Event15th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2012 - Kuching, Sarawak, Malaysia
Duration: 2012 Sept 32012 Sept 7

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7455 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2012
CityKuching, Sarawak

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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