A Heuristic for Domain Independent Planning and its Use in an Enforced Hill-climbing Algorithm

We present a new heuristic method to evaluate planning states, which is based on solving a relaxation of the planning problem. The solutions to the relaxed problem give a good estimate for the length of a real solution, and they can also be used to guide action selection during planning. Using these informations, we employ a search strategy that combines Hill-climbing with systematic search. The algorithm is complete on what we call deadlock-free domains. Though it does not guarantee the solution plans to be optimal, it does find close to optimal plans in most cases. Often, it solves the problems almost without any search at all. In particular, it outperforms all state-of-the-art planners on a large range of domains.