Towards Rational Deployment of Multiple Heuristics in A* / 674
David Tolpin, Tal Beja, Solomon Eyal Shimony, Ariel Felner, Erez Karpas
The obvious way to use several admissible heuristics in A* is to take their maximum. In this paper we aim to reduce the time spent on computing heuristics. We discuss Lazy A*, a variant of A* where heuristics are evaluated lazily: only when they are essential to a decision to be made in the A* search process. We present a new rational meta-reasoning based scheme, Rational Lazy A*, which decides whether to compute the more expensive heuristics at all, based on a myopic value of information estimate. Both methods are examined theoretically. Empirical evaluation on several domains supports the theoretical results, and shows that Lazy A* and Rational Lazy A* are state-of-the-art heuristic combination methods.