Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Weak-commitment search for solving constraint satisfaction problems
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Distributed constraint optimization for medical appointment scheduling
Proceedings of the fifth international conference on Autonomous agents
Dynamic scheduling of a fixed bandwidth communications channel for controlling multiple robots
Proceedings of the fifth international conference on Autonomous agents
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Distributed constraint satisfaction: foundations of cooperation in multi-agent systems
Asynchronous Weak-commitment Search for Solving Distributed Constraint Satisfaction Problems
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
Dynamic Distributed Resource Allocation: A Distributed Constraint Satisfaction Approach
ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
Collectives for multiple resource job scheduling across heterogeneous servers
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Arc-consistency in dynamic constraint satisfaction problems
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
A new method for solving hard satisfiability problems
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
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Constraint Programming research is currently aimed at solving problems in a dynamically changing environment. This paper addresses the problem of solving a Dynamic Distributed Constraint Satisfaction Problem (Dynamic DCSP). The solution proposed is an algorithm implemented in a multi- agent system. A Dynamic DCSP is a problem in which variables, values and constraints are distributed among various agents. Agents can be freely added to or removed from the system. Most advanced applications cannot be represented by DCSPs, but they can be modeled by Dynamic DCSPs. The algorithm described in this paper is an extension of the Asynchronous Weak Commitment Search algorithm (AWCS) originally proposed by Yukoo [10]. The extended algorithm is designed to cope with the dynamically changing parameters of a Dynamic DCSP. The proposed algorithm differs from other Dynamic DCSP algorithms because it allows an unlimited number of changes to any of the variables, values, or constraints. This paper describes an agent system implementing the modified AWCS algorithm and verifies its effectiveness by applying it to a dynamic N-Queens problem. The results prove the applicability of the modified algorithm to Dynamic DCSP.