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Conflict-Directed A* Search for Soft Constraints
[chapter]
2006
Lecture Notes in Computer Science
As many real-world problems involve user preferences, costs, or probabilities, constraint satisfaction has been extended to optimization by generalizing hard constraints to soft constraints. However, as techniques such as local consistency or conflict learning do not easily generalize to optimization, solving soft constraints appears more difficult than solving hard constraints. In this paper, we present an approach to solving soft constraints that exploits this disparity by re-formulating soft
doi:10.1007/11757375_16
fatcat:6fbinxwzava4nn4uwpf7cuxjre