Abstract
Cooperating and sharing resources by creating coalitions of agents are important ways for autonomous agents to execute tasks and to maximize payoff. Such coalitions will form only if each member of a coalition gains more by joining the coalition than it could gain otherwise. There are several ways of creating such coalitions and dividing the joint payoff among the members. In this paper we present algorithms for coalition formation and payoff distribution in nonsuperadditive environments. We focus on a low-complexity kernel-oriented coalition formation algorithm. The properties of this algorithm were examined via simulations. These have shown that the model increases the benefits of the agents within a reasonable time period, and more coalition formations provide more benefits to the agents.
Original language | English |
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Pages (from-to) | 218-251 |
Number of pages | 34 |
Journal | Computational Intelligence |
Volume | 15 |
Issue number | 3 |
DOIs | |
State | Published - Aug 1999 |