Scalable Search in Computer Chess

Scalable Search in Computer Chess: Algorithmic Enhancements and Experiments at High Search Depths

The book presents new results of computer-chess research in the areas of selective forward pruning, the efficient application of game-theoretical knowledge, and the behavior of the search at increasing depths. It shows how to make sophisticated game-tree searchers more scalable at ever higher depths.

Ernst A. Heinz
Scalable Search in Computer Chess
Morgan Kaufmann Publishers (December, 1999)
ISBN: 3528057327

Table of contents

  • Intro
    • 0 Computer-Chess Primer
  • Part I — Forward Pruning without Tears
    • 1 Adaptive Null-Move Pruning
    • 2 Extended Futility Pruning
    • 3 AEL Pruning
  • Part II — Integration of Perfect Knowledge
    • 4 Efficient Interior-Node Recognition
    • 5 Index Schemes of Endgame Databases
    • 6 Knowledgeable Endgame Databases
  • Part III — Search Behaviour at Increasing Depths
    • 7 DarkThought Goes Deep
    • 8 Modeling the “Go Deep” Behaviour
    • 9 Self-Play Experiments Revisited
    • Perspectives on Future Work
  • Part IV — Appendices
    • A How DarkThought Plays Chess
    • B Tournament History of DarkThought
    • C DarkThought and Test Suites
    • D DarkThought at Test Games

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