Chess Skill in Man and Machine

Similar documents
Computer Chess Compendium

COMP219: COMP219: Artificial Intelligence Artificial Intelligence Dr. Annabel Latham Lecture 12: Game Playing Overview Games and Search

Today. Types of Game. Games and Search 1/18/2010. COMP210: Artificial Intelligence. Lecture 10. Game playing

Artificial Intelligence Search III

arxiv: v1 [cs.ai] 8 Aug 2008

COMP219: Artificial Intelligence. Lecture 13: Game Playing

Lecture 14. Questions? Friday, February 10 CS 430 Artificial Intelligence - Lecture 14 1

Chess and Computers. David Levy

Chess Algorithms Theory and Practice. Rune Djurhuus Chess Grandmaster / September 23, 2013

Lecture 7. Review Blind search Chess & search. CS-424 Gregory Dudek

CS 331: Artificial Intelligence Adversarial Search II. Outline

Foundations of AI. 5. Board Games. Search Strategies for Games, Games with Chance, State of the Art. Wolfram Burgard and Luc De Raedt SA-1

Artificial Intelligence. Topic 5. Game playing

Statistics and Computing. Series Editors: J. Chambers D. Hand

TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play

Computational Principles of Mobile Robotics

Adversarial Search and Game- Playing C H A P T E R 6 C M P T : S P R I N G H A S S A N K H O S R A V I

Theory and Practice of Artificial Intelligence

CPS331 Lecture: Search in Games last revised 2/16/10

ARTIFICIAL INTELLIGENCE (CS 370D)

Adversarial Search: Game Playing. Reading: Chapter

CPS 570: Artificial Intelligence Two-player, zero-sum, perfect-information Games

Synthetic Aperture Radar

Foundations of AI. 6. Adversarial Search. Search Strategies for Games, Games with Chance, State of the Art. Wolfram Burgard & Bernhard Nebel

Game-playing: DeepBlue and AlphaGo

Representations of Integers as Sums of Squares

Adversarial Search (Game Playing)

Foundations of Artificial Intelligence

Knowledge-B ased Process Planning for Construction and Manufacturing

Adversarial Search. CS 486/686: Introduction to Artificial Intelligence

Adversarial Search. CMPSCI 383 September 29, 2011

CS 1571 Introduction to AI Lecture 12. Adversarial search. CS 1571 Intro to AI. Announcements

Game Playing. Why do AI researchers study game playing? 1. It s a good reasoning problem, formal and nontrivial.

Rule-Based Expert Systems

Data Structures and Algorithms

Programming Methodology

Foundations of Artificial Intelligence

CSE 40171: Artificial Intelligence. Adversarial Search: Game Trees, Alpha-Beta Pruning; Imperfect Decisions

Google DeepMind s AlphaGo vs. world Go champion Lee Sedol

Adversarial Search. Human-aware Robotics. 2018/01/25 Chapter 5 in R&N 3rd Ø Announcement: Slides for this lecture are here:

Deep Blue System Overview

Programming Project 1: Pacman (Due )

Contents. Foundations of Artificial Intelligence. Problems. Why Board Games?

Algorithms for Data Structures: Search for Games. Phillip Smith 27/11/13

Principles of Data Security

V. Adamchik Data Structures. Game Trees. Lecture 1. Apr. 05, Plan: 1. Introduction. 2. Game of NIM. 3. Minimax

Adversarial Search. Soleymani. Artificial Intelligence: A Modern Approach, 3 rd Edition, Chapter 5

CSC 396 : Introduction to Artificial Intelligence

Adversarial Search. CS 486/686: Introduction to Artificial Intelligence

CS885 Reinforcement Learning Lecture 13c: June 13, Adversarial Search [RusNor] Sec

MyPawns OppPawns MyKings OppKings MyThreatened OppThreatened MyWins OppWins Draws

Optimal Rhode Island Hold em Poker

CS 4700: Foundations of Artificial Intelligence

Foundations of AI. 6. Board Games. Search Strategies for Games, Games with Chance, State of the Art

Adversary Search. Ref: Chapter 5

Lecture Notes in Control and Information Sciences 188. Editors: M. Thoma and W. Wyner

Foundations of Artificial Intelligence

Adversarial Search. Chapter 5. Mausam (Based on slides of Stuart Russell, Andrew Parks, Henry Kautz, Linda Shapiro) 1

CURRENT CHESS PROGRAMS: A SUMMARY OF THEIR POTENTIAL AND LIMITATIONS* P.G. RUSHTON AND T.A. MARSLAND

Outline. Game Playing. Game Problems. Game Problems. Types of games Playing a perfect game. Playing an imperfect game

INTERTEMPORAL PRODUCTION FRONTIERS: WITH DYNAMIC DEA

CS 2710 Foundations of AI. Lecture 9. Adversarial search. CS 2710 Foundations of AI. Game search

Foundations of Artificial Intelligence Introduction State of the Art Summary. classification: Board Games: Overview

Mastering Chess and Shogi by Self- Play with a General Reinforcement Learning Algorithm

Sergey Ablameyko and Tony Pridmore. Machine Interpretation of Line Drawing Images. Technical Drawings, Maps and Diagrams.

Game Engineering CS F-24 Board / Strategy Games

What is Artificial Intelligence? Alternate Definitions (Russell + Norvig) Human intelligence

Artificial Intelligence

CSE 573: Artificial Intelligence Autumn 2010

MATLAB Guide to Finite Elements

Unit-III Chap-II Adversarial Search. Created by: Ashish Shah 1

Game Playing. Philipp Koehn. 29 September 2015

PROCEEDINGS OF SYMPOSIA IN APPLIED MATHEMATICS

AI in Tabletop Games. Team 13 Josh Charnetsky Zachary Koch CSE Professor Anita Wasilewska

1 Introduction. 1.1 Game play. CSC 261 Lab 4: Adversarial Search Fall Assigned: Tuesday 24 September 2013

Games CSE 473. Kasparov Vs. Deep Junior August 2, 2003 Match ends in a 3 / 3 tie!

More on games (Ch )

CS 4700: Foundations of Artificial Intelligence

Further Evolution of a Self-Learning Chess Program

Extended Null-Move Reductions

British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library.

CS2212 PROGRAMMING CHALLENGE II EVALUATION FUNCTIONS N. H. N. D. DE SILVA

PROGRAMS WITH STRINGENT PERFORMANCE OBJECTIVES WILL OFTEN EXHIBIT CHAOTIC BEHAVIOR

MITECS: Chess, Psychology of

Adversarial search (game playing)

Solving Problems by Searching: Adversarial Search

CS440/ECE448 Lecture 9: Minimax Search. Slides by Svetlana Lazebnik 9/2016 Modified by Mark Hasegawa-Johnson 9/2017

Computer Science and Software Engineering University of Wisconsin - Platteville. 4. Game Play. CS 3030 Lecture Notes Yan Shi UW-Platteville

HYBRID NEURAL NETWORK AND EXPERT SYSTEMS

Game Playing State-of-the-Art CSE 473: Artificial Intelligence Fall Deterministic Games. Zero-Sum Games 10/13/17. Adversarial Search

Artificial Intelligence

Bootstrapping from Game Tree Search

Opponent Models and Knowledge Symmetry in Game-Tree Search

- 10. Victor GOLENISHCHEV TRAINING PROGRAM FOR CHESS PLAYERS 2 ND CATEGORY (ELO ) EDITOR-IN-CHIEF: ANATOLY KARPOV. Russian CHESS House

Multisector Growth Models

Handbook of MODERN GRINDING TECHNOLOGY

Adversarial Search and Game Playing. Russell and Norvig: Chapter 5

User's Guide to. Rapid Prototyping. Todd Grimm. Society of Manufacturing Engineers. Association of SME. Dearborn, Michigan

CS 188: Artificial Intelligence Spring Game Playing in Practice

Research Notes in Neural Computing

Transcription:

Chess Skill in Man and Machine

Chess Skill in Man and Machine Edited by Peter W. Frey With 104 Illustrations Springer-Verlag New York Berlin Heidelberg Tokyo

Peter W. Frey Northwestern University CRESAP Laboratory of Neuroscience and Behavior 2021 Sheridan Road Evanston, Illinois 60201 USA AMS Subject Classification: 68-02, 68A45 (C.R.) Computing Classification: 3.64 Library of Congress Cataloging in Publication Data Main entry under title : Chess skill in man and machine. Bibliography: p. Includes index. 1. Chess-Data processing-addresses, essays, lectures. 1. Frey, Peter W. (Peter William), 1942- GV1318.C45 1984 794.1'7 82-19474 1977, 1983 by Springer-Verlag New York Inc. All rights reserved. No part of this book may be translated or reproduced in any form without written permission from Springer-Verlag, 175 Fifth Avenue, New York, New York 10010, USA. Typeset by Maryland Linotype, Baltimore, Maryland. Printed and bound by Halliday Lithograph, Plympton, Massachusetts. This book is also available in a clothbound edition within Texts and Monographs in Computer Science, Chess Skill in Man and Machine, Second Edition. 9 8 7 6 543 2 ISBN-13 : 978-0-387-90815-1 DOl: 1007/978-1-4612-5515-4 e-isbn-13 :978-1-4612-5515-4

This volume is dedicated to my wife, Ruth, and my family, and to my colleagues whose contributions made this volume possible. I am especially indebted to David Slate whose comments and suggestions greatly improved the final version of this book.

Preface Ten years of intensive effort on computer chess have produced notable progress. Although the background information and technical details that were written in 1975 for the first edition of this book are still valid in most essential points, hardware and software refinements have had a major impact on the effectiveness of these ideas. The current crop of chess machines are performing at unexpectedly high levels. The approach epitomized by the series of programs developed by David Slate and Larry Atkin at Northwestern in the middle 1970s (i.e., a sophisticated search algorithm using very little chess knowledge) was expected to reach an asymptbtic level of performance no higher than that of a class A player (USCF rating between 1800 and 2000). This perspective was argued quite vigorously by Eliot Hearst in Chapter 8 of the first edition and was held at that time by many chess experts. Subsequent events have clearly demonstrated that the asymptotic performance level for this type of program it at least as high as the master level (USCF rating between 2200 and 2400). Current discussions now focus upon whether the earlier reservations were wrong in principle or simply underestimated the asymptote. If there is a real barrier which will prevent this type of program from attaining a world championship level of performance, it is not evident from the steady progress which has been observed during the last decade. The second edition of Chess Skill in Man and Machine includes new material highlighting recent developments. A newly added Appendix includes a summary of recent games selected by David Slate which characterize the current level of achievement in machine chess. In addition, the new appendix provides information about the International Computer Chess Association, the establishment of several major prizes for chess programs, and developments in microcomputer chess. The bibliography has also been greatly expanded. The second edition also keeps pace with the development of new ideas with the addition of two chapters. These chapters extend the debate in i- vii

Preface tiated by their predecessors concerning the relative merits of search-based and knowledge-based programs. In Chapter 9, Ken Thompson and Joe Condon describe the architecture and inner workings of BeIIe, the current world champion and the most effective example of a search-intensive program. In Chapter 10, David Wilkins provides information about his program, PARADISE, which is currently the most impressive example of a knowledge-intensive chess program. PARADISE solves deep tactical positions by using a highly focused search. The different approach used by these two programs is emphasized by the number of nodes each examines in analyzing a position. PARADISE generates several hundred nodes, while Belle generates more than ten million. The ideas expressed in these new chapters provide two fascinating perspectives on an issue which is crucial to further developments in computer chess. In its general form, this issue has important ramifications for the entire field of artificial intelligence and will be the subject of active debates for many years. Evanston, IIIinois May, 1982 PETER W. FREY viii

Contents 1 A brief history of the computer chess tournaments: 1970-1975 Benjamin Mittman Introduction Background 2 The tournaments 4 The Soviet Union vs. USA match, 1966-67 6 First United States computer chess championship (New York, 1970) 7 KAISSA vs. the Soviet Public (Moscow, 1972) 12 First world computer chess championship (Stockholm, 1974) 13 Fifth United States computer chess championship (San Diego, 1974) 21 Sixth North American computer chess championship (Minneapolis, 1975) 24 Significance 32 2 Human chess skill Neil Charness Should a computer be more like a man? 34 The choice-of-move problem 35 The role of perception 37 The first few seconds 44 Search through the tree of moves 46 Visualizing positions 47 Evaluation 48 Motivation 50 The road to mastery for man and machine 51 34 ix

Contents 3 An introduction to computer chess Peter W. Frey 54 Machine representation of the chess board 55 Static evaluation functions 60 The look-ahead procedure 61 Backward pruning 65 Quiescence 68 Plausible-move generators 69 FuiI-width searching 73 The opening 77 The endgame 79 Improvement through competition 79 Future prospects 80 4 CHESS 4.5-The Northwestern University chess program David J. Slate and Lawrence R. Atkin 82 Background 82 The development of CHESS 4.0 84 Data base 85 Move generation 89 Tree-searching strategy 91 The evaluation function 93 Tree searching in CHESS 4.5 101 Program performance 113 Conclusions and perspective 113 5 PEASANT: An endgame program for kings and pawns 119 Monroe Newborn The rules of play 120 A description of the program 120 The program's performance 124 Final observations 129 6 Plans, goals, and search strategies for the selection of a move in chess Russell M. Church and Kenneth W. Church Search strategies 134 Search strategies in the movement of the pieces 138 A program to play speed chess 140 131 x

Contents 7 The heuristic search: An alternative to the alpha-beta minimax procedure Larry R. Harris 157 8 Man and machine: Chess achievements and chess thinking Eliot Hearst Introduction 167 Why program a computer to play chess? 168 Past achievements of computer-chess programs 170 Chess thinking: Man versus machine 176 Computer chess: Omens, prospectives, and values 197 Concluding comments 198 167 9 Belle J. H. Condon and Ken Thompson Introduction 201 Background 201 Chess-specific hardware 202 Second generation 204 Third generation 205 The book 208 An experiment 209 Conclusion 210 201 10 Using chess knowledge to reduce search David Wilkins Introduction 211 Overview of PARADISE 213 Concepts and knowledge sources 216 Plans 218 Creating plans 221 How detailed should plans be? 223 Using plans to guide the search 224 A typical medium-sized search 228 Measuring PARADISE's performance 236 Summary and long-term prospects 239 211 Appendix Chess 4.5: Competition in 1976 243 Peter W. Frey The Paul Masson American Chess Championship 243 ACM Computer Chess Championships, 1976 245 xi

Contents Second Appendix Chess 4.5 and Chess 4.6: 248 Competition in 1977 and 1978 Peter W. Frey The Minnesota Open, February, 1977 248 The First Wager Match with Levy, April, 1977 250 The Second World Computer Championship, August, 1977 251 Blitz Chess against Michael Stean in London, September, 1977 253 Twin-Cities Open, April, 1978 254 Walter Browne Simultaneous Exhibition, May, 1978 255 Appendix to the second edition 257 David J. Slate and Peter W. Frey References and bibliography 315 Subject index 325 xii

Chess Skill in Man and Machine