Abstract
As an important area in AI, Distributed Constraint Satisfaction Problems (DisCSPs) can be used to model and solve many problems in multi-agent systems. Concurrent search, newly proposed, is an efficient technique for solving DisCSPs. In this paper, a novel concurrent search algorithm is presented. Dynamic Variable Ordering (DVO) is used in concurrent backtrack search instead of random variable ordering. In order to make DVO effective, domain sizes of unfixed variables are evaluated approximately according to current partial assignments after a variable is assigned. This method can be performed by a single agent and there is no need to send messages during heuristic computation. In addition, a simple look-ahead strategy inspired from centralized constraint programming techniques is added to the improved algorithm. Experiments on randomly generated DisCSPs demonstrate that the algorithm with DVO heuristic and look-ahead strategy can drastically improve performance of concurrent search.
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Gao, J., Sun, J., Zhang, Y. (2007). An Improved Concurrent Search Algorithm for Distributed CSPs. In: Orgun, M.A., Thornton, J. (eds) AI 2007: Advances in Artificial Intelligence. AI 2007. Lecture Notes in Computer Science(), vol 4830. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76928-6_20
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DOI: https://doi.org/10.1007/978-3-540-76928-6_20
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