Cloning Chess Engines by David Levy
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A New Look at the Tayler by David Kane
A New Look at the Tayler by David kane I: Introduction The Tayler Variation (aka the Tayler Opening) is a line that has been unjustly neglected, in my view. The line is of surprisingly recent vintage though it is often confused with the Inverted Hungarian (or Inverted Hanham Defense), a line which shares the same opening moves: 1. e4 e5 2. Nf3 Nc6 3. Be2: The Inverted Hungarian is an old opening, dating back to the 1860ʼs, at least. Tartakower played it a few times in the 1920ʼs with mixed results, using the continuation, 3...Nf6 4. d3: a rather unenterprising setup for White. In 1981 British player, John Tayler (see biographical note), published an article in the British publication Chess (vol. 46) on a line he had developed stemming from the sharp 4. d4!?. This is a move which apparently no one had thought to play before, and one that transforms the sedate Inverted Hungarian into something else altogether. Technically, it is really the Tayler Variation to the Inverted Hungarian Defense rather than the Tayler Opening, though through usage, the terms are interchangeable for all practical purposes. As has been so often the case when it comes to unorthodox lines, I first heard of this opening via Mike Basman when he published a cassette on it back in the early 80ʼs (still available through audiochess.com). Tayler 2 The line stirred some interest at the time but gradually seems to have been forgotten. The final nail in the coffin was probably some light analysis published by Eric Schiller in Gambit Chess Openings (and elsewhere) where he dismisses the line primarily due to his loss in the game Schiller-Martinovsky, Chicago 1986. -
Draft – Not for Circulation
A Gross Miscarriage of Justice in Computer Chess by Dr. Søren Riis Introduction In June 2011 it was widely reported in the global media that the International Computer Games Association (ICGA) had found chess programmer International Master Vasik Rajlich in breach of the ICGA‟s annual World Computer Chess Championship (WCCC) tournament rule related to program originality. In the ICGA‟s accompanying report it was asserted that Rajlich‟s chess program Rybka contained “plagiarized” code from Fruit, a program authored by Fabien Letouzey of France. Some of the headlines reporting the charges and ruling in the media were “Computer Chess Champion Caught Injecting Performance-Enhancing Code”, “Computer Chess Reels from Biggest Sporting Scandal Since Ben Johnson” and “Czech Mate, Mr. Cheat”, accompanied by a photo of Rajlich and his wife at their wedding. In response, Rajlich claimed complete innocence and made it clear that he found the ICGA‟s investigatory process and conclusions to be biased and unprofessional, and the charges baseless and unworthy. He refused to be drawn into a protracted dispute with his accusers or mount a comprehensive defense. This article re-examines the case. With the support of an extensive technical report by Ed Schröder, author of chess program Rebel (World Computer Chess champion in 1991 and 1992) as well as support in the form of unpublished notes from chess programmer Sven Schüle, I argue that the ICGA‟s findings were misleading and its ruling lacked any sense of proportion. The purpose of this paper is to defend the reputation of Vasik Rajlich, whose innovative and influential program Rybka was in the vanguard of a mid-decade paradigm change within the computer chess community. -
March 2020 Uschess.Org the United States’ Largest Chess Specialty Retailer
March 2020 USChess.org The United States’ Largest Chess Specialty Retailer 888.51.CHESS (512.4377) www.USCFSales.com ƩĂĐŬŝŶŐǁŝƚŚŐϮͲŐϰ The 100 Endgames You Must Know Workbook The Modern Way to Get the Upper Hand in Chess WƌĂĐƟĐĂůŶĚŐĂŵĞƐdžĞƌĐŝƐĞƐĨŽƌǀĞƌLJŚĞƐƐWůĂLJĞƌ Dmitry Kryavkin 288 pages - $24.95 Jesus de la Villa 288 pages - $24.95 dŚĞƉĂǁŶƚŚƌƵƐƚŐϮͲŐϰŝƐĂƉĞƌĨĞĐƚǁĂLJƚŽĐŽŶĨƵƐĞLJŽƵƌ ͞/ůŽǀĞƚŚŝƐŬ͊/ŶŽƌĚĞƌƚŽŵĂƐƚĞƌĞŶĚŐĂŵĞƉƌŝŶĐŝƉůĞƐLJŽƵ ŽƉƉŽŶĞŶƚƐĂŶĚĚŝƐƌƵƉƚƚŚĞŝƌƉŽƐŝƟŽŶ͘tŝƚŚůŽƚƐŽĨŝŶƐƚƌƵĐƟǀĞ ǁŝůůŶĞĞĚƚŽƉƌĂĐƟĐĞƚŚĞŵ͘͟ʹNM Han Schut, Chess.com ĞdžĂŵƉůĞƐ'D<ƌLJĂŬǀŝŶƐŚŽǁƐŚŽǁŝƚĐĂŶďĞƵƐĞĚƚŽĚĞĨĞĂƚ ͞dŚĞƉĞƌĨĞĐƚƐƵƉƉůĞŵĞŶƚƚŽĞůĂsŝůůĂ͛ƐŵĂŶƵĂů͘dŽŐĂŝŶ ůĂĐŬŝŶƚŚĞƵƚĐŚ͕ƚŚĞYƵĞĞŶ͛Ɛ'Ăŵďŝƚ͕ƚŚĞEŝŵnjŽͲ/ŶĚŝĂŶ͕ ƐƵĸĐŝĞŶƚŬŶŽǁůĞĚŐĞŽĨƚŚĞŽƌĞƟĐĂůĞŶĚŐĂŵĞƐLJŽƵƌĞĂůůLJŽŶůLJ ƚŚĞ<ŝŶŐ͛Ɛ/ŶĚŝĂŶ͕ƚŚĞ^ůĂǀĂŶĚƚŚĞŶŐůŝƐŚKƉĞŶŝŶŐ͘>ĞĂƌŶ ŶĞĞĚƚǁŽďŽŽŬƐ͘͟ʹIM Herman Grooten, Schaaksite NEW! ƚŚĞƚLJƉŝĐĂůǁĂLJƐƚŽŐĂŝŶƚĞŵƉŝ͕ŬĞĞƉƚŚĞŵŽŵĞŶƚƵŵĂŶĚ ŵĂdžŝŵŝnjĞLJŽƵƌŽƉƉŽŶĞŶƚ͛ƐƉƌŽďůĞŵƐ͘ Strategic Chess Exercises Keep It Simple 1.d4 Find the Right Way to Outplay Your Opponent ^ŽůŝĚĂŶĚ^ƚƌĂŝŐŚƞŽƌǁĂƌĚŚĞƐƐKƉĞŶŝŶŐZĞƉĞƌƚŽŝƌĞĨŽƌtŚŝƚĞ Emmanuel Bricard 224 pages - $24.95 Christof Sielecki 432 pages - $29.95 &ŝŶĂůůLJĂŶĞdžĞƌĐŝƐĞƐŬƚŚĂƚŝƐŶŽƚĂďŽƵƚƚĂĐƟĐƐ͊ ^ŝĞůĞĐŬŝ͛ƐƌĞƉĞƌƚŽŝƌĞǁŝƚŚϭ͘ĚϰŵĂLJďĞĞǀĞŶĞĂƐŝĞƌƚŽ ͞ƌŝĐĂƌĚŝƐĐůĞĂƌůLJĂǀĞƌLJŐŝŌĞĚƚƌĂŝŶĞƌ͘,ĞƐĞůĞĐƚĞĚĂƐƵƉĞƌď ŵĂƐƚĞƌƚŚĂŶŚŝƐϭ͘ĞϰƌĞĐŽŵŵĞŶĚĂƟŽŶƐ͕ďĞĐĂƵƐĞŝƚŝƐƐƵĐŚĂ ƌĂŶŐĞŽĨƉŽƐŝƟŽŶƐĂŶĚĞdžƉůĂŝŶƐƚŚĞƐŽůƵƟŽŶƐĞdžƚƌĞŵĞůLJ ĐŽŚĞƌĞŶƚƐLJƐƚĞŵ͗ƚŚĞŵĂŝŶĐŽŶĐĞƉƚŝƐĨŽƌtŚŝƚĞƚŽƉůĂLJϭ͘Ěϰ͕ ǁĞůů͘͟ʹGM Daniel King Ϯ͘EĨϯ͕ϯ͘Őϯ͕ϰ͘ŐϮ͕ϱ͘ϬͲϬĂŶĚŝŶŵŽƐƚĐĂƐĞƐϲ͘Đϰ͘ ͞&ŽƌĐŚĞƐƐĐŽĂĐŚĞƐƚŚŝƐŬŝƐŶŽƚŚŝŶŐƐŚŽƌƚŽĨƉŚĞŶŽŵĞŶĂů͘͟ ͞Ɛ/ƚŚŝŶŬƚŚĂƚ/ƐŚŽƵůĚŬĞĞƉŵLJĂĚǀŝĐĞ͚ƐŝŵƉůĞ͕͛/ǁŽƵůĚƐĂLJ -
Distributional Differences Between Human and Computer Play at Chess
Multidisciplinary Workshop on Advances in Preference Handling: Papers from the AAAI-14 Workshop Human and Computer Preferences at Chess Kenneth W. Regan Tamal Biswas Jason Zhou Department of CSE Department of CSE The Nichols School University at Buffalo University at Buffalo Buffalo, NY 14216 USA Amherst, NY 14260 USA Amherst, NY 14260 USA [email protected] [email protected] Abstract In our case the third parties are computer chess programs Distributional analysis of large data-sets of chess games analyzing the position and the played move, and the error played by humans and those played by computers shows the is the difference in analyzed value from its preferred move following differences in preferences and performance: when the two differ. We have run the computer analysis (1) The average error per move scales uniformly higher the to sufficient depth estimated to have strength at least equal more advantage is enjoyed by either side, with the effect to the top human players in our samples, depth significantly much sharper for humans than computers; greater than used in previous studies. We have replicated our (2) For almost any degree of advantage or disadvantage, a main human data set of 726,120 positions from tournaments human player has a significant 2–3% lower scoring expecta- played in 2010–2012 on each of four different programs: tion if it is his/her turn to move, than when the opponent is to Komodo 6, Stockfish DD (or 5), Houdini 4, and Rybka 3. move; the effect is nearly absent for computers. The first three finished 1-2-3 in the most recent Thoresen (3) Humans prefer to drive games into positions with fewer Chess Engine Competition, while Rybka 3 (to version 4.1) reasonable options and earlier resolutions, even when playing was the top program from 2008 to 2011. -
A Survey of Monte Carlo Tree Search Methods
IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, VOL. 4, NO. 1, MARCH 2012 1 A Survey of Monte Carlo Tree Search Methods Cameron Browne, Member, IEEE, Edward Powley, Member, IEEE, Daniel Whitehouse, Member, IEEE, Simon Lucas, Senior Member, IEEE, Peter I. Cowling, Member, IEEE, Philipp Rohlfshagen, Stephen Tavener, Diego Perez, Spyridon Samothrakis and Simon Colton Abstract—Monte Carlo Tree Search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling. It has received considerable interest due to its spectacular success in the difficult problem of computer Go, but has also proved beneficial in a range of other domains. This paper is a survey of the literature to date, intended to provide a snapshot of the state of the art after the first five years of MCTS research. We outline the core algorithm’s derivation, impart some structure on the many variations and enhancements that have been proposed, and summarise the results from the key game and non-game domains to which MCTS methods have been applied. A number of open research questions indicate that the field is ripe for future work. Index Terms—Monte Carlo Tree Search (MCTS), Upper Confidence Bounds (UCB), Upper Confidence Bounds for Trees (UCT), Bandit-based methods, Artificial Intelligence (AI), Game search, Computer Go. F 1 INTRODUCTION ONTE Carlo Tree Search (MCTS) is a method for M finding optimal decisions in a given domain by taking random samples in the decision space and build- ing a search tree according to the results. It has already had a profound impact on Artificial Intelligence (AI) approaches for domains that can be represented as trees of sequential decisions, particularly games and planning problems. -
Move Similarity Analysis in Chess Programs
Move similarity analysis in chess programs D. Dailey, A. Hair, M. Watkins Abstract In June 2011, the International Computer Games Association (ICGA) disqual- ified Vasik Rajlich and his Rybka chess program for plagiarism and breaking their rules on originality in their events from 2006-10. One primary basis for this came from a painstaking code comparison, using the source code of Fruit and the object code of Rybka, which found the selection of evaluation features in the programs to be almost the same, much more than expected by chance. In his brief defense, Rajlich indicated his opinion that move similarity testing was a superior method of detecting misappropriated entries. Later commentary by both Rajlich and his defenders reiterated the same, and indeed the ICGA Rules themselves specify move similarity as an example reason for why the tournament director would have warrant to request a source code examination. We report on data obtained from move-similarity testing. The principal dataset here consists of over 8000 positions and nearly 100 independent engines. We comment on such issues as: the robustness of the methods (upon modifying the experimental conditions), whether strong engines tend to play more similarly than weak ones, and the observed Fruit/Rybka move-similarity data. 1. History and background on derivative programs in computer chess Computer chess has seen a number of derivative programs over the years. One of the first was the incident in the 1989 World Microcomputer Chess Cham- pionship (WMCCC), in which Quickstep was disqualified due to the program being \a copy of the program Mephisto Almeria" in all important areas. -
Dream Jobs 2008 Sigrid Close Studies Shooting Stars with the World’S Biggest Radars Australia’S Transcontinental Solar Car Race Wireless’S Virgin Territory
Contents | Zoom in | Zoom out For navigation instructions please click here Search Issue | Next Page THE MAGAZINE OF TECHNOLOGY INSIDERS 02.08 SPECIAL ISSUE: DREAM JOBS 2008 SIGRID CLOSE STUDIES SHOOTING STARS WITH THE WORLD’S BIGGEST RADARS AUSTRALIA’S TRANSCONTINENTAL SOLAR CAR RACE WIRELESS’S VIRGIN TERRITORY Contents | Zoom in | Zoom out For navigation instructions please click here Search Issue | Next Page A SPECTRUM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page BEF MaGS _______________ A SPECTRUM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page BEF MaGS A SPECTRUM Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page BEF MaGS volume 45 number 2 international 02.08 FRONT UPDATE 7 CANCER SCREENING IN A TANGLE A controversial breast-cancer technology is coming to market. By Morgen E. Peck 8 BIG JUMP IN MICRO- PROCESSOR MATH 9 REINVENTING THE WHEEL 10 CAN WIND ENERGY KEEP GROWING? 11 ELECTRONIC GENE THERAPY 12 BRAKE-BY-WIRE FOR FREIGHT TRAINS 14 THE BIG PICTURE Cranial calculations. OPINION 5 SPECTRAL LINES Format wars at the Consumer Electronics Show: one down, more to go. 6 FORUM The (relative) safety of Tasers, the tainting of online gaming, and measuring entropy. 21 TECHNICALLY SPEAKING The snowclone: A higher-order cliché? THE EXTRA SPECIAL REPORT By Paul McFedries MILE: David Downey designs and then fi eld- 23 DREAM JOBS 2008 DEPARTMENTS tests fi tness When your day job is this much fun, can you really call it “work”? 3 CONTRIBUTORS products; Roger Hill builds 4 BACK STORY computers to 40 GADGETS GAB AT 60 GHz track penguins in To juggle gigabits of high-defi nition video, wireless networks 17 CAREERS Antarctica; must move way, way up the spectrum. -
New Architectures in Computer Chess Ii New Architectures in Computer Chess
New Architectures in Computer Chess ii New Architectures in Computer Chess PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Tilburg, op gezag van de rector magnificus, prof. dr. Ph. Eijlander, in het openbaar te verdedigen ten overstaan van een door het college voor promoties aangewezen commissie in de aula van de Universiteit op woensdag 17 juni 2009 om 10.15 uur door Fritz Max Heinrich Reul geboren op 30 september 1977 te Hanau, Duitsland Promotor: Prof. dr. H.J.vandenHerik Copromotor: Dr. ir. J.W.H.M. Uiterwijk Promotiecommissie: Prof. dr. A.P.J. van den Bosch Prof. dr. A. de Bruin Prof. dr. H.C. Bunt Prof. dr. A.J. van Zanten Dr. U. Lorenz Dr. A. Plaat Dissertation Series No. 2009-16 The research reported in this thesis has been carried out under the auspices of SIKS, the Dutch Research School for Information and Knowledge Systems. ISBN 9789490122249 Printed by Gildeprint © 2009 Fritz M.H. Reul All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronically, mechanically, photocopying, recording or otherwise, without prior permission of the author. Preface About five years ago I completed my diploma project about computer chess at the University of Applied Sciences in Friedberg, Germany. Immediately after- wards I continued in 2004 with the R&D of my computer-chess engine Loop. In 2005 I started my Ph.D. project ”New Architectures in Computer Chess” at the Maastricht University. In the first year of my R&D I concentrated on the redesign of a computer-chess architecture for 32-bit computer environments. -
A Chess Engine
A Chess Engine Paul Dailly Dominik Gotojuch Neil Henning Keir Lawson Alec Macdonald Tamerlan Tajaddinov University of Glasgow Department of Computing Science Sir Alwyn Williams Building Lilybank Gardens Glasgow G12 8QQ March 18, 2008 Abstract Though many computer chess engines are available, the number of engines using object orientated approaches to the problem is minimal. This report documents an implementation of an object oriented chess engine. Traditionally, in order to gain the advantage of speed, the C language is used for implementation, however, being an older language, it lacks many modern language features. The chess engine documented within this report uses the modern Java language, providing features such as reflection and generics that are used extensively, allowing for complex but understandable code. Also of interest are the various depth first search algorithms used to produce a fast game, and the numerous functions for evaluating different characteristics of the board. These two fundamental components, the evaluator and the analyser, combine to produce a fast and relatively skillful chess engine. We discuss both the design and implementation of the engine, along with details of other approaches that could be taken, and in what manner the engine could be expanded. We conclude by examining the engine empirically, and from this evaluation, reflecting on the advantages and disadvantages of our chosen approach. Education Use Consent We hereby give our permission for this project to be shown to other University of Glasgow students and to be distributed in an electronic format. Please note that you are under no obligation to sign this declaration, but doing so would help future students. -
FUEGO – an Open-Source Framework for Board Games and Go Engine Based on Monte-Carlo Tree Search
FUEGO – An Open-source Framework for Board Games and Go Engine Based on Monte-Carlo Tree Search Markus Enzenberger, Martin Muller,¨ Broderick Arneson and Richard Segal Abstract—FUEGO is both an open-source software frame- available source code such as Hoffmann’s FF [20] have had work and a state of the art program that plays the game of a similarly massive impact, and have enabled much followup Go. The framework supports developing game engines for full- research. information two-player board games, and is used successfully in UEGO a substantial number of projects. The FUEGO Go program be- F contains a game-independent, state of the art came the first program to win a game against a top professional implementation of MCTS with many standard enhancements. player in 9×9 Go. It has won a number of strong tournaments It implements a coherent design, consistent with software against other programs, and is competitive for 19 × 19 as well. engineering best practices. Advanced features include a lock- This paper gives an overview of the development and free shared memory architecture, and a flexible and general current state of the FUEGO project. It describes the reusable components of the software framework and specific algorithms plug-in architecture for adding domain-specific knowledge in used in the Go engine. the game tree. The FUEGO framework has been proven in applications to Go, Hex, Havannah and Amazons. I. INTRODUCTION The main innovation of the overall FUEGO framework may lie not in the novelty of any of its specific methods and Research in computing science is driven by the interplay algorithms, but in the fact that for the first time, a state of of theory and practice. -
Some Chess-Specific Improvements for Perturbation-Based Saliency Maps
Some Chess-Specific Improvements for Perturbation-Based Saliency Maps Jessica Fritz Johannes Furnkranz¨ Johannes Kepler University Johannes Kepler University Linz, Austria Linz, Austria [email protected] juffi@faw.jku.at Abstract—State-of-the-art game playing programs do not pro- vide an explanation for their move choice beyond a numerical score for the best and alternative moves. However, human players want to understand the reasons why a certain move is considered to be the best. Saliency maps are a useful general technique for this purpose, because they allow visualizing relevant aspects of a given input to the produced output. While such saliency maps are commonly used in the field of image classification, their adaptation to chess engines like Stockfish or Leela has not yet seen much work. This paper takes one such approach, Specific and Relevant Feature Attribution (SARFA), which has previously been proposed for a variety of game settings, and analyzes it specifically for the game of chess. In particular, we investigate differences with respect to its use with different chess Fig. 1: SARFA Example engines, to different types of positions (tactical vs. positional as well as middle-game vs. endgame), and point out some of the approach’s down-sides. Ultimately, we also suggest and evaluate a neural networks [19], there is also great demand for explain- few improvements of the basic algorithm that are able to address able AI models in other areas of AI, including game playing. some of the found shortcomings. An approach that has recently been proposed specifically for Index Terms—Explainable AI, Chess, Machine learning games and related agent architectures is specific and relevant feature attribution (SARFA) [15].1 It has been shown that it I. -
Rybka Investigation and Summary of Findings for the ICGA Mark Lefler, Robert Hyatt, Harvey Williamson and ICGA Panel Members 12 May 2011
Rybka Investigation and Summary of Findings for the ICGA Mark Lefler, Robert Hyatt, Harvey Williamson and ICGA panel members 12 May 2011 1. Background 1.1 Purpose: To investigate claims that the chess playing program Rybka is a derivative of the chess programs Fruit and Crafty and violated International Computer Games Association (ICGA) Tournament rules. Rybka is a program by Vasik Rajlich. Fruit was written by Fabien Letouzey. Crafty was written by Robert Hyatt. 1.2 Allegations. Allegations have surfaced that Rybka 1.0 beta and later versions are derivatives of Fruit 2.1. Fruit 2.1 source code was distributed with a specific license in the copying.txt file. Part of this license reads: "For example, if you distribute copies of such a program, whether gratis or for a fee, you must give the recipients all the rights that you have. You must make sure that they, too, receive or can get the source code. And you must show them these terms so they know their rights." Allegations point out that by distributing Rybka, if it is based on Fruit, this GNU license was violated (http://icga.wikispaces.com/Open+letter+to+the+ICGA+about+the+Rybka- Fruit+issue). If versions of Rybka are derived from Fruit and participated in ICGA tournaments, then Rybka has also violated ICGA Tournament Rules. Specifically, the rules state: "Each program must be the original work of the entering developers. Programming teams whose code is derived from or including game-playing code written by others must name all other authors, or the source of such code, in the details of their submission form.