A space-time tradeoff for memory-based heuristics

被引:0
作者
Holte, RC [1 ]
Hernádvölgyi, IT [1 ]
机构
[1] Univ Ottawa, Sch Informat Technol & Engn, Ottawa, ON K1N 6N5, Canada
来源
SIXTEENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-99)/ELEVENTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE (IAAI-99) | 1999年
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D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A memory-based heuristic is a function, h(s), stored in the form of a lookup table (pattern database): h(s) is computed by mapping s to an index and then retrieving the appropriate entry in the table. (Korf 1997) conjectures for search using memory-based heuristics that m.t is a constant, where m is the size of the heuristic's lookup table and t is search time. In this paper we present a method for automatically generating memory-based heuristics and use this to test Korf's conjecture in a large-scale experiment. Our results confirm that there is a direct relationship between m and t.
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页码:704 / 709
页数:6
相关论文
共 11 条
  • [1] Culberson J. C., 1996, Advances in Artificial Intelligence. 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI'96. Proceedings, P402
  • [2] PERIMETER SEARCH
    DILLENBURG, JF
    NELSON, PC
    [J]. ARTIFICIAL INTELLIGENCE, 1994, 65 (01) : 165 - 178
  • [3] STRIPS - NEW APPROACH TO APPLICATION OF THEOREM PROVING TO PROBLEM SOLVING
    FIKES, RE
    NILSSON, NJ
    [J]. ARTIFICIAL INTELLIGENCE, 1971, 2 (3-4) : 189 - 208
  • [4] HERNADVOLGYI IT, 1999, TR9904 U OTT SCH INF
  • [5] Holte RC, 1996, PROCEEDINGS OF THE THIRTEENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE, VOLS 1 AND 2, P530
  • [6] KAINDL H, 1995, P 14 INT JOINT C ART, P236
  • [7] Korf R. E., 1997, P 14 NAT C ART INT, P700
  • [8] Korf RE, 1998, FIFTEENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-98) AND TENTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICAL INTELLIGENCE (IAAI-98) - PROCEEDINGS, P305
  • [9] DEPTH-1ST ITERATIVE-DEEPENING - AN OPTIMAL ADMISSIBLE TREE-SEARCH
    KORF, RE
    [J]. ARTIFICIAL INTELLIGENCE, 1985, 27 (01) : 97 - 109
  • [10] PRIEDITIS AE, 1993, MACH LEARN, V12, P117, DOI 10.1007/BF00993063