Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Consistency restoriation and explanations in dynamic CSPs----application to configuration
Artificial Intelligence
Multi-agent oriented constraint satisfaction
Artificial Intelligence
Algorithms for Distributed Constraint Satisfaction: A Review
Autonomous Agents and Multi-Agent Systems
Dynamic Variable Ordering in CSPs
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
Constraint Processing
Introduction: special issue on distributed constraint satisfaction
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Concurrent search for distributed CSPs
Artificial Intelligence
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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.