An empirical analysis of some heuristic features for local search in LPG
Alfonso Gerevini, Alessandro Saetti, Ivan Serina · 2004
LPG is a planner that performed very well in the last Interna-tional planning competition (2002). The system is based on a stochastic local search procedure, and it incorporates several heuristic features. In this paper we experimentally analyze the most important of them with the goal of understanding and evaluating their impact on the performance of the plan-ner. In particular, we examine three heuristic functions for evaluating the search neighborhood and some settings of the “noise ” parameter, that randomizes the next search step for escaping from local minima. Moreover, we present and ana-lyze additional heuristic techniques for restricting the search neighborhood and for selecting the next inconsistency to han-dle. The experimental results show that the use of such tech-niques significantly improves the performance of the planner.