Abstract
W. Yeoh, S. Koenig and X. Sun. Trading Off Solution Cost for Smaller Runtime in DCOP Search Algorithms [Short Paper]. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2008.Abstract: 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 no worse than them for ADOPT.
There is also a workshop publication with additional experimental results available.
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