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Lesson Plans for Go in Schools
Go Lesson Plans 1 Lesson Plans for Go in Schools By Gordon E. Castanza, Ed. D. October 19, 2011 Published By Rittenberg Consulting Group 7806 108th St. NW Gig Harbor, WA 98332 253-853-4831 ©Gordon E. Castanza, Ed. D. 10/19/11 DRAFT Go Lesson Plans 2 Table of Contents Acknowledgements ......................................................................................................................... 4 Purpose/Rationale ........................................................................................................................... 5 Lesson Plan One ............................................................................................................................. 7 Basic Ideas .................................................................................................................................. 7 Introduction ............................................................................................................................... 11 The Puzzle ................................................................................................................................. 13 Surround to Capture .................................................................................................................. 14 First Capture Go ........................................................................................................................ 16 Lesson Plan Two ........................................................................................................................... 19 Units & -
Complete Journal (PDF)
B RITISH J OURNAL Number 140 Spring 2007 Price £3.50 British Go Journal 140 Spring 2007 CONTENTS EDITORIAL 2 UK NEWS Tony Atkins 3 OUTGOING PRESIDENT’S REPORT, 2005-6 Simon Goss 9 10 YEARS AGO Tony Atkins 11 THREE PEAKS Ian Marsh 13 REFEREEING QUESTION Nick Wedd 14 BRITISH CHAMPIONSHIP 2006 17 COUNTING BY AREA AND TERRITORY Andrei Sokolov 18 WORLD NEWS Tony Atkins 21 REVIEW:BADUK MADE FUN AND EASY Ian Davis 25 AMATEUR PAIR GO CHAMPIONSHIPS Natasha Regan 26 VISIT TO KOREA -OCTOBER 2006 T Mark Hall 29 KOREA Tony Atkins 33 HOW TO GIVE A GAME REVIEW Nick Wedd 35 WEAK GROUP THEORY Ron Bell 37 UK CLUBS LIST 43 GLOSSARY OF GO TERMS 44 Copyright c 2007 British Go Association. Articles may be reproduced for the purposes of promoting Go and ’not for profit’ providing the British Go Journal is attributed as the source and the permission of the Editor and of the articles’ author(s) have been sought and obtained. Views expressed are not necessarily those of the BGA or of the Editor. USEFUL WEB AND EMAIL ADDRESSES Journal comments and contributions: [email protected] Email for general BGA enquiries: [email protected] BGA website: http://www.britgo.org/ BGA email list: [email protected] used for general discussion and announcements - control from: http://three.pairlist.net/mailman/listinfo/gotalk For discussion of how the BGA operates: [email protected] http://two.pairlist.net/mailman/listinfo/bga-policy 1 EDITORIAL [email protected] Welcome to my first attempt at producing your Journal. -
GO WINDS Play Over 1000 Professional Games to Reach Recent Sets Have Focused on "How the Pros 1-Dan, It Is Said
NEW FROM YUTOPIAN ENTERPRISES GO GAMES ON DISK (GOGoD) SOFTWARE GO WINDS Play over 1000 professional games to reach Recent sets have focused on "How the pros 1-dan, it is said. How about 6-dan? Games of play the ...". So far there are sets covering the Go on Disk now offers over 6000 professional "Chinese Fuseki" Volume I (a second volume Volume 2 Number 4 Winter 1999 $3.00 games on disk, games that span the gamut of is in preparation), and "Nirensei", Volumes I go history - featuring players that helped and II. A "Sanrensei" volume is also in define the history. preparation. All these disks typically contain All game collections come with DOS or 300 games. Windows 95 viewing software, and most The latest addition to this series is a collections include the celebrated Go Scorer in "specialty" item - so special GoGoD invented which you can guess the pros' moves as you a new term for it. It is the "Sideways Chinese" play (with hints if necessary) and check your fuseki, which incorporates the Mini-Chinese score. pattern. Very rarely seen in western The star of the collection may well be "Go publications yet played by most of the top Seigen" - the lifetime games (over 800) of pros, this opening is illustrated by over 130 perhaps the century's greatest player, with games from Japan, China and Korea. Over more than 10% commented. "Kitani" 1000 half have brief comments. The next specialty makes an ideal matching set - most of the item in preparation is a set of games featuring lifetime games of his legendary rival, Kitani unusual fusekis - this will include rare New Minoru. -
Curriculum Guide for Go in Schools
Curriculum Guide 1 Curriculum Guide for Go In Schools by Gordon E. Castanza, Ed. D. October 19, 2011 Published By: Rittenberg Consulting Group 7806 108th St. NW Gig Harbor, WA 98332 253-853-4831 © 2005 by Gordon E. Castanza, Ed. D. Curriculum Guide 2 Table of Contents Acknowledgements ......................................................................................................................... 4 Purpose and Rationale..................................................................................................................... 5 About this curriculum guide ................................................................................................... 7 Introduction ..................................................................................................................................... 8 Overview ................................................................................................................................. 9 Building Go Instructor Capacity ........................................................................................... 10 Developing Relationships and Communicating with the Community ................................. 10 Using Resources Effectively ................................................................................................. 11 Conclusion ............................................................................................................................ 11 Major Trends and Issues .......................................................................................................... -
Learning to Play the Game of Go
Learning to Play the Game of Go James Foulds October 17, 2006 Abstract The problem of creating a successful artificial intelligence game playing program for the game of Go represents an important milestone in the history of computer science, and provides an interesting domain for the development of both new and existing problem-solving methods. In particular, the problem of Go can be used as a benchmark for machine learning techniques. Most commercial Go playing programs use rule-based expert systems, re- lying heavily on manually entered domain knowledge. Due to the complexity of strategy possible in the game, these programs can only play at an amateur level of skill. A more recent approach is to apply machine learning to the prob- lem. Machine learning-based Go playing systems are currently weaker than the rule-based programs, but this is still an active area of research. This project compares the performance of an extensive set of supervised machine learning algorithms in the context of learning from a set of features generated from the common fate graph – a graph representation of a Go playing board. The method is applied to a collection of life-and-death problems and to 9 × 9 games, using a variety of learning algorithms. A comparative study is performed to determine the effectiveness of each learning algorithm in this context. Contents 1 Introduction 4 2 Background 4 2.1 Go................................... 4 2.1.1 DescriptionoftheGame. 5 2.1.2 TheHistoryofGo ...................... 6 2.1.3 Elementary Strategy . 7 2.1.4 Player Rankings and Handicaps . 7 2.1.5 Tsumego .......................... -
Computer Go: an AI Oriented Survey
Computer Go: an AI Oriented Survey Bruno Bouzy Université Paris 5, UFR de mathématiques et d'informatique, C.R.I.P.5, 45, rue des Saints-Pères 75270 Paris Cedex 06 France tel: (33) (0)1 44 55 35 58, fax: (33) (0)1 44 55 35 35 e-mail: [email protected] http://www.math-info.univ-paris5.fr/~bouzy/ Tristan Cazenave Université Paris 8, Département Informatique, Laboratoire IA 2, rue de la Liberté 93526 Saint-Denis Cedex France e-mail: [email protected] http://www.ai.univ-paris8.fr/~cazenave/ Abstract Since the beginning of AI, mind games have been studied as relevant application fields. Nowadays, some programs are better than human players in most classical games. Their results highlight the efficiency of AI methods that are now quite standard. Such methods are very useful to Go programs, but they do not enable a strong Go program to be built. The problems related to Computer Go require new AI problem solving methods. Given the great number of problems and the diversity of possible solutions, Computer Go is an attractive research domain for AI. Prospective methods of programming the game of Go will probably be of interest in other domains as well. The goal of this paper is to present Computer Go by showing the links between existing studies on Computer Go and different AI related domains: evaluation function, heuristic search, machine learning, automatic knowledge generation, mathematical morphology and cognitive science. In addition, this paper describes both the practical aspects of Go programming, such as program optimization, and various theoretical aspects such as combinatorial game theory, mathematical morphology, and Monte- Carlo methods. -
Go Books Detail
Evanston Go Club Ian Feldman Lending Library A Compendium of Trick Plays Nihon Ki-in In this unique anthology, the reader will find the subject of trick plays in the game of go dealt with in a thorough manner. Practically anything one could wish to know about the subject is examined from multiple perpectives in this remarkable volume. Vital points in common patterns, skillful finesse (tesuji) and ordinary matters of good technique are discussed, as well as the pitfalls that are concealed in seemingly innocuous positions. This is a gem of a handbook that belongs on the bookshelf of every go player. Chapter 1 was written by Ishida Yoshio, former Meijin-Honinbo, who intimates that if "joseki can be said to be the highway, trick plays may be called a back alley. When one masters the alleyways, one is on course to master joseki." Thirty-five model trick plays are presented in this chapter, #204 and exhaustively analyzed in the style of a dictionary. Kageyama Toshiro 7 dan, one of the most popular go writers, examines the subject in Chapter 2 from the standpoint of full board strategy. Chapter 3 is written by Mihori Sho, who collaborated with Sakata Eio to produce Killer of Go. Anecdotes from the history of go, famous sayings by Sun Tzu on the Art of Warfare and contemporary examples of trickery are woven together to produce an entertaining dialogue. The final chapter presents twenty-five problems for the reader to solve, using the knowledge gained in the preceding sections. Do not be surprised to find unexpected booby traps lurking here also. -
Cognitive Reflection and Theory of Mind of Go Players Marc Oliver Rieger1and Mei Wang2
RESEARCH ARTICLE ADVANCES IN COGNITIVE PSYCHOLOGY Cognitive Reflection and Theory of Mind of Go Players Marc Oliver Rieger1and Mei Wang2 1 University of Trier 2 WHU – Otto Beisheim School of Management ABSTRACT Go is a classical Chinese mind game and a highly popular intellectual pursuit in East Asia. In a survey KEYWORDS at two Go tournaments (one of them the largest in Europe), we measured cognitive reflection and cognitive reflection test decision in strategic games (using the classical “beauty contest” game) (N = 327). We found that Go theory of mind players in our survey had outstanding average cognitive reflection test (CRT) scores: 2.51 among all patience participants and 2.80 among players of high master level (dan). This value easily outperforms previ- board games ous measurements, for example, of undergraduates at top universities. The CRT score was closely Go related to the playing strength, but not to the frequency of playing. On the other hand, frequent weiqi players tended to have higher theory of mind, regardless of their playing strengths. However, self- baduk reported patience was not statistically significantly correlated with Go strength or playing frequency. chess INTRODUCTION Human behavior is influenced by cognitive ability. Traditionally, these playing strategic games that require adopting the other person’s point abilities have been summarized in one dimension, intelligence, but of view, for example, the famous “beauty contest game or “Keynesian subsequent research focused on finding more and more facets of intel- beauty contest” (Nagel, 1995).1 The name of this game is inspired by ligence that are important for specific tasks. -
Table of Contents
Jay Burmeister Janet Wiles Departments of Computer Science and Psychology The University of Queensland, QLD 4072, Australia Technical Report 339, Department of Computer Science, The University of Queensland, 1995 (This document is - permanently - under construction). See also: Jay Burmeister’s PhD Thesis (2000) Table of Contents 1.0 Introduction 2.0 The Game of Go 2.1 Liberties and Capture 2.1.1 Suicide 2.2 Strings 2.3 Eyes 2.3.1 Dead or Alive 2.3.2 False Eyes 2.3.3 Seki 2.4 Repetition of Board Positions - Ko 2.5 Sente and Gote 2.6 Ladders 2.6.1 Snapbacks 2.7 Links 2.8 Groups 2.9 Armies 2.10 Winning the Game 2.11 The Go Handicap and Ranking System 3.0 The Challenge of Programming Go 3.1 A Comparison of Chess and Go 3.2 The Complexity of Go 3.3 Why Go Cannot be Programmed Like Chess 4.0 History of the Computer Go Field 4.1 Academic Work 4.1.1 Zobrist 4.1.2 Ryder 4.1.3 Reitman and Wilcox 4.1.4 Other Academic Work 4.2 Programs 4.2.1 The Many Faces of Go 4.2.1.1 G2 4.2.1.2 Cosmos 4.2.1.3 Many Faces of Go 4.2.2 Go4++ 4.2.2.1 Candidate Move Generation 4.2.2.2 Evaluation Function 4.2.2.3 Performance and Timeline 4.2.3 Handtalk 4.3 Computer Go Competitions 4.3.1 The Ing Prize 5.0 What's in a Go Program? 6.0 Performance of Current Programs 6.1 Program versus Program Performance 6.2 Program versus Human Performance 7.0 Future Improvements in Performance 8.0 Go and Computer Go Resources on the Internet 8.1 Computer Go related Internet Resources 8.1.1 Anonymous FTP Archive and Mirror Sites 8.1.2 The Internet Go Server (IGS) 8.1.3 Game Record Formats -
The Way to Go Is a Copyrighted Work
E R I C M A N A G F O O N How to U I O N D A T www.usgo.org www.agfgo.org play the Asian game of Go The Way to by Karl Baker American Go Association Box 397 Old Chelsea Station New York, NY 10113 GO Legal Note: The Way To Go is a copyrighted work. Permission is granted to make complete copies for personal use. Copies may be distributed freely to others either in print or electronic form, provided no fee is charged for distribution and all copies contain this copyright notice. The Way to Go by Karl Baker American Go Association Box 397 Old Chelsea Station New York, NY 10113 http://www.usgo.org Cover print: Two Immortals and the Woodcutter A watercolor by Seikan. Date unknown. How to play A scene from the Ranka tale: Immortals playing go as the the ancient/modern woodcutter looks on. From Japanese Prints and the World of Go by William Pinckard at: Asian Game of Go http://www.kiseido.com/printss/cover.htm Dedicated to Ann All in good time there will come a climax which will lift one to the heights, but first a foundation must be laid, INSPIRED BY HUNDREDS broad, deep and solid... OF BAFFLED STUDENTS Winfred Ernest Garrison © Copyright 1986, 2008 Preface American Go Association The game of GO is the essence of simplicity and the ultimate in complexity all at the same time. It is taught earnestly at military officer training schools in the Orient, as an exercise in military strategy. -
Move Prediction in the Game of Go
Move Prediction in the Game of Go A Thesis presented by Brett Alexander Harrison to Computer Science in partial fulfillment of the honors requirements for the degree of Bachelor of Arts Harvard College Cambridge, Massachusetts April 1, 2010 Abstract As a direct result of artificial intelligence research, computers are now expert players in a variety of popular games, including Checkers, Chess, Othello (Reversi), and Backgammon. Yet one game continues to elude the efforts of computer scientists: Go, also known as Igo in Japan, Weiqi in China, and Baduk in Korea. Due in part to the strategic complexity of Go and the sheer number of moves available to each player, most typical game-playing algorithms have failed to be effective with Go. Even state-of-the-art computer Go programs are weaker than high-ranking amateurs. Thus Go provides the perfect framework for devel- oping and testing new ideas in a variety of fields in computer science, including algorithms, computational game theory, and machine learning. In this thesis, we explore the problem of move prediction in the game of Go. The move prediction problem asks how we can build a program which trains on Go games in order to predict the moves of professional and high-ranking amateur players in other Go games. An accurate move predictor could serve as a powerful component of Go-playing programs, since it can be used to reduce the branching factor in game tree search and can be used as an effective move ordering heuristic. Our first main contribution to this field is the creation of a novel move prediction system, based on a naive Bayes model, which builds upon the work of several previous move prediction systems. -
What Is the Project Title
Artificial Intelligence for Go CIS 499 Senior Design Project Final Report Kristen Ying Advisors: Dr. Badler and Dr. Likhachev University of Pennsylvania PROJECT ABSTRACT Go is an ancient board game, originating in China – where it is known as weiqi - before 600 B.C. It spread to Japan (where it is also known as Go), to Korea as baduk, and much more recently to Europe and America [American Go Association]. This game, in which players take turn placing stones on a 19x19 board in an attempt to capture territory, is polynomial-space hard [Reyzin]. Checkers is also polynomial-space hard, and is a solved problem [Schaeffer]. However, the sheer magnitude of options (and for intelligent algorithms, sheer number of possible strategies) makes it infeasible to create even passable novice AI with an exhaustive pure brute-force approach on modern hardware. The board is 19 x19, which, barring illegal moves, allows for about 10171 possible ways to execute a game. This number is about 1081 times greater than the believed number of elementary particles contained in the known universe [Keim]. Previously investigated approaches to creating AI for Go include human-like models such as pattern recognizers and machine learning [Burmeister and Wiles]. There are a number of challenges to these approaches, however. Machine learning algorithms can be very sensitive to the data and style of play with which they are trained, and approaches modeling human thought can be very sensitive to the designer‟s perception of how one thinks during a game. Professional Go players seem to have a very intuitive sense of how to play, which is difficult to model.