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The 12Th Top Chess Engine Championship
TCEC12: the 12th Top Chess Engine Championship Article Accepted Version Haworth, G. and Hernandez, N. (2019) TCEC12: the 12th Top Chess Engine Championship. ICGA Journal, 41 (1). pp. 24-30. ISSN 1389-6911 doi: https://doi.org/10.3233/ICG-190090 Available at http://centaur.reading.ac.uk/76985/ It is advisable to refer to the publisher’s version if you intend to cite from the work. See Guidance on citing . To link to this article DOI: http://dx.doi.org/10.3233/ICG-190090 Publisher: The International Computer Games Association All outputs in CentAUR are protected by Intellectual Property Rights law, including copyright law. Copyright and IPR is retained by the creators or other copyright holders. Terms and conditions for use of this material are defined in the End User Agreement . www.reading.ac.uk/centaur CentAUR Central Archive at the University of Reading Reading’s research outputs online TCEC12: the 12th Top Chess Engine Championship Guy Haworth and Nelson Hernandez1 Reading, UK and Maryland, USA After the successes of TCEC Season 11 (Haworth and Hernandez, 2018a; TCEC, 2018), the Top Chess Engine Championship moved straight on to Season 12, starting April 18th 2018 with the same divisional structure if somewhat evolved. Five divisions, each of eight engines, played two or more ‘DRR’ double round robin phases each, with promotions and relegations following. Classic tempi gradually lengthened and the Premier division’s top two engines played a 100-game match to determine the Grand Champion. The strategy for the selection of mandated openings was finessed from division to division. -
Chess Engine Using Deep Reinforcement Learning Kamil Klosowski
Chess Engine Using Deep Reinforcement Learning Kamil Klosowski 916847 May 2019 Abstract Reinforcement learning is one of the most rapidly developing areas of Artificial Intelligence. The goal of this project is to analyse, implement and try to improve on AlphaZero architecture presented by Google DeepMind team. To achieve this I explore different architectures and methods of training neural networks as well as techniques used for development of chess engines. Project Dissertation submitted to Swansea University in Partial Fulfilment for the Degree of Bachelor of Science Department of Computer Science Swansea University Declaration This work has not previously been accepted in substance for any degree and is not being currently submitted for any degree. May 13, 2019 Signed: Statement 1 This dissertation is being submitted in partial fulfilment of the requirements for the degree of a BSc in Computer Science. May 13, 2019 Signed: Statement 2 This dissertation is the result of my own independent work/investigation, except where otherwise stated. Other sources are specifically acknowledged by clear cross referencing to author, work, and pages using the bibliography/references. I understand that fail- ure to do this amounts to plagiarism and will be considered grounds for failure of this dissertation and the degree examination as a whole. May 13, 2019 Signed: Statement 3 I hereby give consent for my dissertation to be available for photocopying and for inter- library loan, and for the title and summary to be made available to outside organisations. May 13, 2019 Signed: 1 Acknowledgment I would like to express my sincere gratitude to Dr Benjamin Mora for supervising this project and his respect and understanding of my preference for largely unsupervised work. -
Elo World, a Framework for Benchmarking Weak Chess Engines
Elo World, a framework for with a rating of 2000). If the true outcome (of e.g. a benchmarking weak chess tournament) doesn’t match the expected outcome, then both player’s scores are adjusted towards values engines that would have produced the expected result. Over time, scores thus become a more accurate reflection DR. TOM MURPHY VII PH.D. of players’ skill, while also allowing for players to change skill level. This system is carefully described CCS Concepts: • Evaluation methodologies → Tour- elsewhere, so we can just leave it at that. naments; • Chess → Being bad at it; The players need not be human, and in fact this can facilitate running many games and thereby getting Additional Key Words and Phrases: pawn, horse, bishop, arbitrarily accurate ratings. castle, queen, king The problem this paper addresses is that basically ACH Reference Format: all chess tournaments (whether with humans or com- Dr. Tom Murphy VII Ph.D.. 2019. Elo World, a framework puters or both) are between players who know how for benchmarking weak chess engines. 1, 1 (March 2019), to play chess, are interested in winning their games, 13 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn and have some reasonable level of skill. This makes 1 INTRODUCTION it hard to give a rating to weak players: They just lose every single game and so tend towards a rating Fiddly bits aside, it is a solved problem to maintain of −∞.1 Even if other comparatively weak players a numeric skill rating of players for some game (for existed to participate in the tournament and occasion- example chess, but also sports, e-sports, probably ally lose to the player under study, it may still be dif- also z-sports if that’s a thing). -
Super Human Chess Engine
SUPER HUMAN CHESS ENGINE FIDE Master / FIDE Trainer Charles Storey PGCE WORLD TOUR Young Masters Training Program SUPER HUMAN CHESS ENGINE Contents Contents .................................................................................................................................................. 1 INTRODUCTION ....................................................................................................................................... 2 Power Principles...................................................................................................................................... 4 Human Opening Book ............................................................................................................................. 5 ‘The Core’ Super Human Chess Engine 2020 ......................................................................................... 6 Acronym Algorthims that make The Storey Human Chess Engine ......................................................... 8 4Ps Prioritise Poorly Placed Pieces ................................................................................................... 10 CCTV Checks / Captures / Threats / Vulnerabilities ...................................................................... 11 CCTV 2.0 Checks / Checkmate Threats / Captures / Threats / Vulnerabilities ............................. 11 DAFiii Attack / Features / Initiative / I for tactics / Ideas (crazy) ................................................. 12 The Fruit Tree analysis process ............................................................................................................ -
Project: Chess Engine 1 Introduction 2 Peachess
P. Thiemann, A. Bieniusa, P. Heidegger Winter term 2010/11 Lecture: Concurrency Theory and Practise Project: Chess engine http://proglang.informatik.uni-freiburg.de/teaching/concurrency/2010ws/ Project: Chess engine 1 Introduction From the Wikipedia article on Chess: Chess is a two-player board game played on a chessboard, a square-checkered board with 64 squares arranged in an eight-by-eight grid. Each player begins the game with sixteen pieces: one king, one queen, two rooks, two knights, two bishops, and eight pawns. The object of the game is to checkmate the opponent’s king, whereby the king is under immediate attack (in “check”) and there is no way to remove or defend it from attack on the next move. The game’s present form emerged in Europe during the second half of the 15th century, an evolution of an older Indian game, Shatranj. Theoreticians have developed extensive chess strategies and tactics since the game’s inception. Computers have been used for many years to create chess-playing programs, and their abilities and insights have contributed significantly to modern chess theory. One, Deep Blue, was the first machine to beat a reigning World Chess Champion when it defeated Garry Kasparov in 1997. Do not worry if you are not familiar with the rules of chess! You are not asked to change the methods which calculate the moves, nor the internal representation of boards or moves, nor the scoring of boards. 2 Peachess Peachess is a chess engine written in Java. The implementation consists of several components. 2.1 The chess board The chess board representation stores the actual state of the game. -
The TCEC Cup 2 Report
TCEC Cup 2 Article Accepted Version The TCEC Cup 2 report Haworth, G. and Hernandez, N. (2019) TCEC Cup 2. ICGA Journal, 41 (2). pp. 100-107. ISSN 1389-6911 doi: https://doi.org/10.3233/ICG-190104 Available at http://centaur.reading.ac.uk/81390/ It is advisable to refer to the publisher’s version if you intend to cite from the work. See Guidance on citing . Published version at: https://content.iospress.com/articles/icga-journal/icg190104 To link to this article DOI: http://dx.doi.org/10.3233/ICG-190104 Publisher: The International Computer Games Association All outputs in CentAUR are protected by Intellectual Property Rights law, including copyright law. Copyright and IPR is retained by the creators or other copyright holders. Terms and conditions for use of this material are defined in the End User Agreement . www.reading.ac.uk/centaur CentAUR Central Archive at the University of Reading Reading’s research outputs online TCEC Cup 2 Guy Haworth and Nelson Hernandez1 Reading, UK and Maryland, USA The knockout format of TCEC Cup 1 (Haworth and Hernandez, 2019a/b) was well received by its audience and was adopted as a regular interlude between the TCEC Seasons’ Division P and Superfinal. TCEC Cup 2 was nested within TCEC14 (Haworth and Hernandez, 2019c/d) and began on January 17th 2019 with 32 chess engines and only a few minor changes from the inaugural Cup event. The ‘standard pairing’ was again used, with seed s playing seed 26-r-s+1 in round r if the wins all go to the higher seed. -
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. -
Chess Assistant 15 Is a Unique Tool for Managing Chess Games and Databases, Playing Chess Online, Analyzing Games, Or Playing Chess Against the Computer
Chess Assistant 15 is a unique tool for managing chess games and databases, playing chess online, analyzing games, or playing chess against the computer. The package includes the best chess engine – Houdini 4 UCI, Chess Opening Encyclopedia, a powerful search system, a unique Tree mode, databases of 6.2 million games in total (as of November 1, 2014), 1-year Premium Game Service (3000 new games each week by Internet), twelve months of free access (1-year membership) at ChessOK Playing Zone. Houdini 4 is the World’s strongest chess engine, capable of supporting up to 32 cores and 32 GB of hash. You can connect Houdini 4 UCI engine to ChessOK Aquarium, Fritz and ChessBase. Houdini 4 – The World Rating Lists Leader Chess Assistant 15 comes with the Houdini 4 chess engine. Houdini 4 leads most independent computer chess rating lists. No serious chess player can be without Houdini 4! Opening Studies – Stay Organized with Opening Tables Chess Opening Encyclopedia contains rich theoretical material on all openings. It contains over 8.000 annotations from GM Kalinin and 40 million evaluations by the strongest engines. The detailed key system for all openings can be edited to suit your needs. Opening Tables is a revolutionary way of creating, maintaining and studying your opening repertoire. Base your studies on the Opening Encyclopedia, customize it with your own moves and evaluations, enhance your favorite variations or create your own private opening repertoire. Working on your opening repertoire finally becomes the creative and enjoyable task it should be! Opening Test Mode allows you to test your knowledge and skills in openings. -
Portable Game Notation Specification and Implementation Guide
11.10.2020 Standard: Portable Game Notation Specification and Implementation Guide Standard: Portable Game Notation Specification and Implementation Guide Authors: Interested readers of the Internet newsgroup rec.games.chess Coordinator: Steven J. Edwards (send comments to [email protected]) Table of Contents Colophon 0: Preface 1: Introduction 2: Chess data representation 2.1: Data interchange incompatibility 2.2: Specification goals 2.3: A sample PGN game 3: Formats: import and export 3.1: Import format allows for manually prepared data 3.2: Export format used for program generated output 3.2.1: Byte equivalence 3.2.2: Archival storage and the newline character 3.2.3: Speed of processing 3.2.4: Reduced export format 4: Lexicographical issues 4.1: Character codes 4.2: Tab characters 4.3: Line lengths 5: Commentary 6: Escape mechanism 7: Tokens 8: Parsing games 8.1: Tag pair section 8.1.1: Seven Tag Roster 8.2: Movetext section 8.2.1: Movetext line justification 8.2.2: Movetext move number indications 8.2.3: Movetext SAN (Standard Algebraic Notation) 8.2.4: Movetext NAG (Numeric Annotation Glyph) 8.2.5: Movetext RAV (Recursive Annotation Variation) 8.2.6: Game Termination Markers 9: Supplemental tag names 9.1: Player related information www.saremba.de/chessgml/standards/pgn/pgn-complete.htm 1/56 11.10.2020 Standard: Portable Game Notation Specification and Implementation Guide 9.1.1: Tags: WhiteTitle, BlackTitle 9.1.2: Tags: WhiteElo, BlackElo 9.1.3: Tags: WhiteUSCF, BlackUSCF 9.1.4: Tags: WhiteNA, BlackNA 9.1.5: Tags: WhiteType, BlackType -
Determining If You Should Use Fritz, Chessbase, Or Both Author: Mark Kaprielian Revised: 2015-04-06
Determining if you should use Fritz, ChessBase, or both Author: Mark Kaprielian Revised: 2015-04-06 Table of Contents I. Overview .................................................................................................................................................. 1 II. Not Discussed .......................................................................................................................................... 1 III. New information since previous versions of this document .................................................................... 1 IV. Chess Engines .......................................................................................................................................... 1 V. Why most ChessBase owners will want to purchase Fritz as well. ......................................................... 2 VI. Comparing the features ............................................................................................................................ 3 VII. Recommendations .................................................................................................................................... 4 VIII. Additional resources ................................................................................................................................ 4 End of Table of Contents I. Overview Fritz and ChessBase are software programs from the same company. Each has a specific focus, but overlap in some functionality. Both programs can be considered specialized interfaces that sit on top a -
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. -
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.