TY - GEN
T1 - A kernel-oriented model for autonomous-agent coalition-formation in general environments
AU - Shehory, Onn
AU - Kraus, Sarit
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1996.
PY - 1996
Y1 - 1996
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/84949470632
U2 - 10.1007/3-540-61314-5_19
DO - 10.1007/3-540-61314-5_19
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AN - SCOPUS:84949470632
SN - 3540613145
SN - 9783540613145
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 31
EP - 45
BT - Distributed Artificial Intelligence
A2 - Zhang, Chengqi
A2 - Lukose, Dickson
PB - Springer Verlag
T2 - 1st Australian Workshop on Distributed Artificial Intelligence, DAI 1995
Y2 - 13 November 1995 through 13 November 1995
ER -