Coalition Formation Meets Information Theory

The process of coalition formation, where distinct autonomous agents come together to act as a coherent group is an important form of interaction in multiagent systems. Previous work has focused on developing coalition formation algorithms which seek to maximize some coalition structure valuation function V (CS). However, for many real-world systems, evaluation of V (CS) must be done empirically, which can be time-consuming, and when evaluation of V (CS) becomes too expensive, value-based coalition formation algorithms can become unattractive. In this work we present a algorithm for forming high value coalition structures when direct evaluation of V (CS) is not feasible. We present the IBCF (Information-Based Coalition Formation) algorithm, which does not try to directly maximize V (CS), but instead seeks to form coalitions which possess maximum amounts of information about how environmental states and agent actions relate to external reward. Such information maximization strategies h...

• Type: Conference
• Year: 2006
• Where: FLAIRS
• Authors: Victor Palmer, Thomas R. Ioerger
• Keywords: Artificial Intelligence, Coalition Formation, Coalition Formation Algorithms, Coalition Structures, FLAIRS 2006