HPP: A Heuristic Progressive Planner

In the last decade three main ideas have revolutionized the Artificial Intelligence (AI) planning methods: the plan graph search structure, planning as satisfiability and the search guided by a heuristic function calculated from a relaxed plan. In this paper we present a new planner, named HPP (Heuristic Progressive Planner), that has been implemented using several ideas extracted from other heuristic planners. However, HPP includes a new module (analysis reachability module) that is able to exclude irrelevant domain-dependent operators for the planning process. The analysis performed by this module avoids to expand several parts of the search tree allowing to solve more problems. Finally, the HPP planner has been incorporated into a distributed multi-agent system to allow exploring in parallel subsets of the search space. The experimental results show how the HPP planner outperforms FF and state of the art planners evaluated in the number of problems solved or the number of steps.