How local is that optimum? k-optimality for DCOP

In multi-agent systems where sets of joint actions (JAs) are generated, metrics are needed to evaluate these sets and efficiently allocate resources for the many JAs. For the case where a JA set can be represented by multiple solutions to a DCOP, we introduce koptimality as a metric that captures desirable properties of diversity and relative quality, and apply results from coding theory to obtain upper bounds on cardinalities of k-optimal JA sets. These bounds can help choose the appropriate level of k-optimality for settings with fixed resources and help determine appropriate resource allocation for settings where a fixed level of k-optimality is desired. Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence; I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search General Terms Design, Theory Keywords constraint reasoning, DCOP, multiagent systems, k-optimality

• Type: Conference
• Year: 2005
• Where: ATAL
• Authors: Jonathan P. Pearce, Rajiv T. Maheswaran, Milind Tambe
• Keywords: Artificial Intelligence, ATAL 2005, Ja Sets, K-optimal Ja Sets