Combining Adaptive Noise and Look-Ahead in Local Search for SAT

Abstract. The adaptive noise mechanism was introduced in Novelty+ to automatically adapt noise settings during the search [4]. The local search algorithm G2 WSAT deterministically exploits promising decreasing variables to reduce randomness and consequently the dependence on noise parameters. In this paper, we first integrate the adaptive noise mechanism in G2 WSAT to obtain an algorithm adaptG2 WSAT, whose performance suggests that the deterministic exploitation of promising decreasing variables cooperates well with this mechanism. Then, we propose an approach that uses look-ahead for promising decreasing variables to further reinforce this cooperation. We implement this approach in adaptG2 WSAT, resulting in a new local search algorithm called adaptG2 WSATP . Without any manual noise or other parameter tuning, adaptG2 WSATP shows generally good performance, compared with G2 WSAT with approximately optimal static noise settings, or is sometimes even better than G2 WSAT. In addition, ...

• Type: Conference
• Year: 2007
• Where: SAT
• Authors: Chu Min Li, Wanxia Wei, Harry Zhang
• Keywords: Adaptive Noise Mechanism, Local Search Algorithms, Promising Decreasing Variables, SAT 2007