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Title: Finding optimal solutions to the twenty-four puzzle

We have found the first optimal solutions to random instances of the Twenty-Four Puzzle, the 5 x 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 finite-state machine. Finally, we observe that as heuristic search problems are scaled up, more powerful heuristic functions become both necessary and cost-effective.
Authors:
;  [1]
  1. Univ. of California, Los Angeles, CA (United States)
Publication Date:
OSTI Identifier:
430804
Report Number(s):
CONF-960876-
CNN: Grant IRI-9119825; TRN: 96:006521-0179
Resource Type:
Conference
Resource Relation:
Conference: 13. National conference on artifical intelligence and the 8. Innovative applications of artificial intelligence conference, Portland, OR (United States), 4-8 Aug 1996; Other Information: PBD: 1996; Related Information: Is Part Of Proceedings of the thirteenth national conference on artificial intelligence and the eighth innovative applications of artificial intelligence conference. Volume 1 and 2; PB: 1626 p.
Publisher:
American Association for Artificial Intelligence, Menlo Park, CA (United States)
Country of Publication:
United States
Language:
English
Subject:
99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; ARTIFICIAL INTELLIGENCE; INFORMATION RETRIEVAL; GAME THEORY; LEARNING