Experimental studies of variable selection strategies based on constraint weights
Journal of Algorithms
A general, fully distributed multi-agent planning algorithm
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A novel approach for dynamic authorisation planning in constrained workflow systems
Proceedings of the 6th International Conference on Security of Information and Networks
Diagnosing correctness of semantic workflow models
Data & Knowledge Engineering
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In this paper we explore the number of consistency checks made by a tree search in order to solve binary constraint satisfaction problems. We show analytically and experimentally that the two principles of first trying the places most likely to fail and remembering what has been done to avoid repeating the same mistake twice improve the standard backtracking search. We experimentally show that a lookahead procedure called forward checking (to remember the future) which employs the most likely to fail principle performs better than standard backtracking, Ullman's, Waltz's, Mackworth's, and Haralick's discrete relaxation in all cases tested, and better than Gaschnigs backmarking in the larger problems.