Fast Planning in Domains with Derived Predicates: An Approach Based on Rule-Action Graphs and Local Search

The ability to express “derived predicates” in the formalization of a planning domain is both practically and theoretically important. In this paper, we propose an approach to planning with derived predicates where the search space consists of “Rule-Action Graphs”, particular graphs of actions and rules representing derived predicates. We present some techniques for representing rules and reasoning with them, which are integrated into a method for planning through local search and rule-action graphs. We also propose some new heuristics for guiding the search, and some experimental results illustrating the performance of our approach. Our proposed techniques are implemented in a planner that took part in the fourth International Planning Competition showing good performance in many benchmark problems.