Finding optimal solutions to the twenty-four puzzle

  • Authors:

  • Richard E. Korf;Larry A. Taylor

  • Affiliations:

  • Computer Science Department, University of California, Los Angeles, Los Angeles, CA;Computer Science Department, University of California, Los Angeles, Los Angeles, CA

  • Venue:
  • AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
  • Year:
  • 1996

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Abstract

We have found the first optimal solutions to random instances of the Twenty-Four Puzzle, the 5 × 5 version of the well-known sliding-tile puzzles. Our new contribution to this problem is a more powerful admissible heuristic function. We present a general theory for the automatic discovery of such heuristics, which is based on considering multiple subgoals simultaneously. In addition, we apply a technique for pruning duplicate nodes in depth-first search using a finitestate machine. Finally, we observe that as heuristic search problems are scaled up, more powerful heuristic functions become both necessary and cost-effective.