A kernel-oriented model for autonomous-agent coalition-formation in general environments

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2 Scopus citations

Abstract

An important way for autonomous agents to execute tasks and to maximize payoff is to share resources and cooperate on task execution by creating coalitions of agents. Among individual rational agents, such coalitions will form if, and only if, each member of a coalition gains more if it joins the coalition than it could gain previously. There are several models of creating such coalitions and dividing the joint payoff among the members. In this paper we present a model for coalition formation and payoff distribution in general environments. We focus on a reduced complexity kernel-oriented coalition formation model. The model is partitioned into two levels — a social level and a strategic level. This partition enables one to distinguish between regulations that must be agreed upon and are forced by the designers of the agents, and strategies by which each agent acts and that can be adopted at will.

Original languageEnglish
Title of host publicationDistributed Artificial Intelligence
Subtitle of host publicationArchitecture and Modelling - 1st Australian Workshop on DAI, Proceedings
EditorsChengqi Zhang, Dickson Lukose
PublisherSpringer Verlag
Pages31-45
Number of pages15
ISBN (Print)3540613145, 9783540613145
DOIs
StatePublished - 1996
Event1st Australian Workshop on Distributed Artificial Intelligence, DAI 1995 - Canberra, Australia
Duration: 13 Nov 199513 Nov 1995

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1087
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st Australian Workshop on Distributed Artificial Intelligence, DAI 1995
Country/TerritoryAustralia
CityCanberra
Period13/11/9513/11/95

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1996.

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