TY - JOUR AU - Rintanen, Jussi PY - 2011/08/04 Y2 - 2024/03/29 TI - Planning with Specialized SAT Solvers JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 25 IS - 1 SE - New Scientific and Technical Advances in Research DO - 10.1609/aaai.v25i1.7962 UR - https://ojs.aaai.org/index.php/AAAI/article/view/7962 SP - 1563-1566 AB - <p> Logic, and declarative representation of knowledge in general, have long been a preferred framework for problem solving in AI. However, specific subareas of AI have been eager to abandon general-purpose knowledge representation in favor of methods that seem to address their computational core problems better. In planning, for example, state-space search has in the last several years been preferred to logic-based methods such as SAT. In our recent work, we have demonstrated that the observed performance differences between SAT and specialized state-space search methods largely go back to the difference between a blind (or at least planning-agnostic) and a planning-specific search method. If SAT search methods are given even simple heuristics which make the search goal-directed, the efficiency differences disappear. </p> ER -