Abstract: In this paper, we propose a new approach to establish Singleton Arc Consistency (SAC) on constraint networks. While the principle of existing SAC algorithms involves performing a breadth-first search up to a depth equal to 1, the principle of the two algorithms introduced in this paper involves performing several runs of a greedy search (where at each step, arc consistency is maintained). It is then an original illustration of applying inference (i.e. establishing singleton arc consistency) by search. Using a greedy search allows benefiting from the incrementality of arc consistency, learning relevant information from conflicts and, potentially finding solution(s) during the inference process. Further-more, both space and time complexities are quite competitive.
0 Replies
Loading