Ernst A. Heinz

Scalable Search in Computer Chess (eBook, PDF)

Algorithmic Enhancements and Experiments at High Search Depths

• Format: PDF

Produktbeschreibung

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 behaviour of the search at increasing depths. It shows how to make sophisticated game-tree searchers more scalable at ever higher depths. Throughout the whole book, the high-speed and master-strength chess program "DarkThought" serves as a realistic test vehicle to conduct numerous experiments at unprecedented search depths. The extensive experimental evaluations provide convincing empirical evidence for the practical usefulness of the presented techniques. Advantages: - presentation of advanced and brand-new research results in computer chess (e.g. selective pruning and other search enhancements, improved endgame databases, etc.) - numerous experiments at unprecedented search depths - extensive experimental evaluation - practical usefulness of new techniques proven within strong state-of-the-art chess program "DarkThought" - includes detailed implementation skeletons in ANSI-C - contains concise introductions into the game of chess and the basics of computer chess in general

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Produktdetails

• Verlag: Vieweg+Teubner Verlag
• Seitenzahl: 270
• Erscheinungstermin: 1. Dezember 2013
• Englisch
• ISBN-13: 9783322901781
• Artikelnr.: 53146650

Autorenporträt

Ernst A. Heinz earned his "Doktor" (Ph.D.) degree with "Auszeichnung" (summa cum laude) from the University of Karlsruhe, Germany, in July 1999 and joined the Laboratory for Computer Science at the Massachusetts Institute of Technology (M.I.T.), Boston/Cambridge, USA, as a Postdoctoral Fellow later that year. ----- German ----- Ernst A. Heinz bestand seine Doktorprüfung an der Universität Karlsruhe im Juli 1999 mit Auszeichnung und ist seit Herbst 1999 als "Postdoctoral Fellow" am "Laboratory of Computer Science" des "Massachussetts Institute of Technology" (M.I.T.) in Boston/Cambridge, USA.

Inhaltsangabe

Adaptive Null-Move Pruning - Extended Futility Pruning - Efficient Interior-Node - Recognition - Index Schemes of Endgame Databases - Knowledgeable Endgame Databases - 'DarkThought' Goes Deep - Self-Play Experiments Revisited