Concise characteristic function representations in coalitional games based on agent types

Forming effective coalitions is a major research challenge in AI and multi-agent systems (MAS). Thus, coalitional games, including Coalition Structure Generation (CSG), have been attracting considerable attention from the AI research community. Traditionally, the input of a coalitional game is a black-box function called a characteristic function. A range of previous studies have found that many problems in coalitional games tend to be computationally intractable when the input is a black-box function. Recently, several concise representation schemes for a characteristic function have been proposed. Although these schemes are effective for reducing the representation size, most problems remain computationally intractable. In this paper, we develop a new concise representation scheme based on the idea of agent types. Intuitively, a type represents a set of agents, which are recognized as having the same contribution. This representation can be exponentially more concise than existing c...

• Type: Journal
• Year: 2011
• Where: ATAL
• Authors: Suguru Ueda, Makoto Kitaki, Atsushi Iwasaki, Makoto Yokoo
• Keywords: ATAL 2011, Coalitional Games, Concise Representation, Intelligent Agents, Polynomial Time