Trading off solution cost for smaller runtime in DCOP search algorithms

Distributed Constraint Optimization (DCOP) is a key technique for solving multiagent coordination problems. Unfortunately, finding minimal-cost DCOP solutions is NP-hard. We therefore propose two mechanisms that trade off the solution costs of two DCOP search algorithms (ADOPT and BnB-ADOPT) for smaller runtimes, namely the Inadmissible Heuristics Mechanism and the Relative Error Mechanism. The solution costs that result from these mechanisms are bounded by a more meaningful quantity than the solution costs that result from the existing Absolute Error Mechanism since they both result in solution costs that are larger than minimal by at most a user-specified percentage. Furthermore, the Inadmissible Heuristics Mechanism experimentally dominates both the Absolute Error Mechanism and the Relative Error Mechanism for BnB-ADOPT and is generally no worse than them for ADOPT. Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence; I.2.8 [Arti...

• Type: Conference
• Year: 2008
• Where: ATAL
• Authors: William Yeoh, Sven Koenig, Xiaoxun Sun
• Keywords: ATAL 2008, Error Mechanism, Intelligent Agents, Relative Error Mechanism, Solution Costs