Towards rational deployment of multiple heuristics in A*

  • Authors:

  • David Tolpin;Tal Beja;Solomon Eyal Shimony;Ariel Felner;Erez Karpas

  • Affiliations:

  • CS Department, Ben-Gurion University, Israel;CS Department, Ben-Gurion University, Israel;CS Department, Ben-Gurion University, Israel;ISE Department, Ben-Gurion University, Israel;Faculty of IE&M, Technion, Israel

  • Venue:
  • IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

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.