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Studies in Human and Computer Go: Assessing the Game of Go As a Research Domain for Cognitive Science

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Studies in Human and Computer Go: Assessing the Game of Go As a Research Domain for Cognitive Science Studies in Human and Computer Go: Assessing the Game of Go as a Research Domain for Cognitive Science Jay Madison Burmeister BSc BA (Hons) A thesis submitted for the degree of Doctor of Philosophy School of Computer Science and Electrical Engineering and School of Psychology The University of Queensland Australia October 2000 Statement of Originality The work presented in this thesis is, to the best of my knowledge and belief, original, except as acknowledged in the text, and the material has not been submitted, either in whole or in part, for a degree at this or any other university1. Jay Burmeister October 2000 1 I gratefully acknowledge the author of the Statement of Originality whose identity is unfortunately shrouded in the mists of time. i ii Abstract This thesis assesses the game of Go as a research domain for Cognitive Science by investigating some of the research issues within the domain of Go, and in particular, by assessing Go as a research domain for both Artificial Intelligence and Cognitive Psychology. The following general assessment questions were used: • To what extent does the domain of Go facilitate the investigation of research questions? • What type of research issues can be investigated within the domain of Go? • Does investigation within the domain of Go give rise to further interesting research questions? • Do useful generalisations arise from research conducted within the domain of Go? What types of generalisations can be made? • In what ways does the domain of Go facilitate an exchange of ideas between disciplines? The methodology used to answer these questions involved case studies of Computer Go programs and experimental studies in the memory field. In Computer Go the research issues addressed were related to knowledge, search and their interaction. The AI techniques used in Computer Chess are generally not successful in Computer Go. It is commonly believed that the large branching factor in Go is the reason why brute-force search techniques used in Computer Chess do not work in Computer Go. However, the main reason for the failure is that static evaluation of Go positions is not possible due to the necessity of life and death analysis (although the large branching factor is certainly a contributing factor to the failure). Case studies of two Go programs (Many Faces of Go and Go4++) as well as an overview of the current top Go programs are presented Together they show how the techniques developed by the Computer Go community address the difficulties associated with programming a game that resists the brute-force search approach. The memory research issues addressed the use of Go for studying the factors that affect memory for Go moves and the extent to which inference impacts on memory performance for sequences of Go moves. Three experimental studies comprising experiments and case studies were iii conducted using beginner, experienced, and master Go players as participants. The experimental studies were instrumental in the development of a new experimental paradigm for testing memory performance for sequences of moves from a Go game, and in particular, the development of two new experimental tasks, namely the sequential pennies-guessing task and the sequential construction task. An extension of this paradigm led to the development of a potential technique for learning Go involving the use of interactive memory tasks. The results of the experimental studies indicated that inference impacts to some extent on memory performance, that memory for sequences of moves is related to Go skill, and that Go is a better domain than chess for investigating memory for sequences. Following the assessment of Go as a research domain for Artificial Intelligence and Cognitive Psychology, this thesis concludes that: • the game of Go provides a good research domain for Artificial Intelligence, facilitating investigation into areas such as planning, problem solving, pattern recognition, and opponent modelling; and • the game of Go provides a good research domain for Cognitive Psychology, facilitating investigation into areas such as memory, implicit learning, pattern recognition, perceptual learning, problem solving, and attention. Based on these conclusions, this thesis finds that: The game of Go provides a good research domain for Cognitive Science. iv List of Publications Burmeister, J. and Wiles, J. (1995) Accessing Go and Computer Go resources on the Internet. In H. Matsubara, editor, Proceedings of the Second Game Programming Workshop in Japan ‘95, pages 75 - 84, Kanagawa. Computer Shogi Association. Burmeister, J., Wiles, J. and Purchase, H. (1995) The integration of cognitive knowledge into perceptual representations in Computer Go. In H. Matsubara, editor, Proceedings of the Second Game Programming Workshop in Japan ‘95, pages 85 - 94, Kanagawa. Computer Shogi Association. Burmeister, J. and Wiles, J. (1995) The challenge of Go as a domain: A comparison between Go and chess. In Proceedings of the Third Australian and New Zealand Conference on Intelligent Information Systems, pages 181 - 186, Perth. IEEE Western Australia Section. (refereed) Burmeister, J., Wiles, J. and Purchase, H. (1995) On relating local and global factors: A case study from the game of Go. In Proceedings of the Third Australian and New Zealand Conference on Intelligent Information Systems, pages 187 - 192, Perth. IEEE Western Australia Section. (refereed) Burmeister, J. and Wiles, J. (1996) The use of inferential information in remembering Go positions. In H. Matsubara, editor, Proceedings of the Third Game Programming Workshop in Japan ‘96, pages 56 - 65, Kanagawa. Computer Shogi Association. Burmeister, J., Wiles, J. and Purchase, H. (1999) The integration of cognitive knowledge into a perceptual representation: Lessons from human and Computer Go. In J. Wiles and T. Dartnall, editors, Perspectives on Cognitive Science: Theories, Experiments and Foundations, Volume II, pages 239 - 257. Ablex, Connecticut. (refereed) Burmeister, J. and Wiles, J. (1999) AI techniques used in Computer Go. In R. Heath, B. Hayes, A. Heathcote and C. Hooker, editors, Proceedings of the Fourth Conference of the Australasian Cognitive Science Society. University of Newcastle. (refereed) Burmeister, J., Saito, Y, Yoshikawa, A. and Wiles, J. (2000) Memory performance of master Go players. In H. J. van den Herik and H. Iida, editors, Games in AI Research, pages 271 - 286. Universiteit Maastricht. (refereed) v vi Acknowledgements I am grateful to my wife, Sharyn, and my daughter, Casey, for providing me with their love and support throughout my PhD. I dedicate this thesis to them in honour of their sacrifices which made its completion possible. I am grateful to Janet Wiles, my supervisor, mentor, and friend, who deserves much of the credit for this project and thesis. Janet sparked my initial interest in research, and taught me how to conduct and communicate research. Janet’s guidance, wisdom, support, and friendship has made it possible for me to achieve my potential. I would like to thank my associate supervisor, Mike Humphreys, for his help with the Cognitive Psychology side of this project. My thanks also go to my auditor, Roger Duke, for making report time more a pleasure than a pressure, and for being an understanding and supportive boss during the final stages of writing my thesis. I am grateful to Helen Purchase for her Honours supervision during Janet’s absence and for her contributions to the early publications that resulted from my Honours work and developed into my PhD. I would like to thank Robert Thomas and Jennifer Downie for their help, without which I most likely would not have been able to finish this project. I am grateful to Andrew Hussey for his assistance with writing the software used to conduct the experiments. This thesis document has benefited through the critical analysis and comments of Scott Bolland, Kerry Chalmers, Simon Dennis, Jennifer Hallinan, Mike Humphreys, Andrew Hussey, Mike Norris, Guy Smith, and Brad Tonkes, for which I am grateful. I was very fortunate to be able to spend 3 months conducting research in Japan at NTT. I am grateful to my colleagues, Yasuki Saito and Atsushi Yoshikawa, for sharing their experience, knowledge, and facilities with me, and for providing the opportunity to meet members of the Go and Computer Go communities. I also appreciate Yaski-san, Yoshikawa-san, and the all the Kame-G members for making my stay not only a rewarding research visit, but also a wonderful vii time that I will never forget. Special thanks to Makiko Ishikawa for the friendly way in which she helped me to cope with my domestic and administrative concerns, and Takehiko Ohno for his technical support. I am also grateful to NTT for the financial support the provided for me during my stay in Japan. The Go and Computer Go communities have been very good to me. I would particularly like to thank David Fotland, Mick Reiss, Martin Müller, Ken Chen, Tristan Cazenave, and Zhixing Chen for sharing the details of their Go programs and assisting me to communicate them. I would like to thank Masahiro Okasaki of the Go Culture Study Group for making the 9x9 professional games available to me and Peter Robinson for providing me with the Shusaku book. I would also like to thank Darren Cook, Chihiro Mizuuchi, Hidekazu Takagi and Yasutoshi Yasuda for the help they gave me while I was in Japan. Thanks to my office mates, Rafael Brander, Rachael Gibson, Peta Wyeth, and Leesa Murray, and my lunch mates, Andrew Hussey, Anthony MacDonald, and David Leadbetter, who provided me with encouragement and attentive ears to pour out my troubles and share my triumphs. Thanks to the members of the Cognitive Science Research Group, the Department of Computer Science and Electrical Engineering, and the School of Psychology for their helpful discussions, and for providing a stimulating environment in which to conduct my research. Thanks also to the administrative and technical staff of the Department of Computer Science and Electrical Engineering, and the School of Psychology for their help.
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