Deciding roles for efficient team formation by parameter learning

Dai Hamada, Toshiharu Sugawara

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

2 Citations (Scopus)

Abstract

We propose a learning method for efficient team formation 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 effective team formation to do tasks has 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 which other agents should be selected as team members and which team it should join. Our experiments demonstrated that the numbers of tasks executed by successfully generated teams increased by approximately 17% compared with a conventional method.

Original languageEnglish
Title of host publicationAgent and Multi-Agent Systems
Subtitle of host publicationTechnologies and Applications - 6th KES International Conference, KES-AMSTA 2012, Proceedings
Pages544-553
Number of pages10
DOIs
Publication statusPublished - 2012 Jul 10
Event6th KES International Conference on Agent and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2012 - Dubrovnik, Croatia
Duration: 2012 Jun 252012 Jun 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7327 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th KES International Conference on Agent and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2012
CountryCroatia
CityDubrovnik
Period12/6/2512/6/27

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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