CSP Search Algorithms with Responsibility Sets and Kernels

A CSP lookahead search algorithm, like FC or MAC, explores a search tree during its run. Every node of the search tree can be associated with a CSP created by the refined domains of unassigned variables. If the algorithm detects that the CSP associated with a node is insoluble, the node becomes a dead-end. A strategy of pruning ”by analogy” states that the current node of the search tree can be discarded if the CSP associated with it is ”more constrained” than a CSP associated with some dead-end node. In this paper we present a method of pruning based on the above strategy. The information about the CSPs associated with dead-end nodes is kept in the structures called responsibility set and kernel. The method that uses these structures for pruning is termed Responsibility set, Kernel, Propagation RKP. The resulting combined algorithms are FC-RKP and MAC-RKP. Under certain restrictions, FC-RKP is shown theoretically to simulate FC-CBJ. Experimental evaluation is presented demonstrating that MAC-RKP outperforms MAC-CBJ on random CSPs and on random graph coloring problems.