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On Competency of Go Players: a Computational Approach

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On Competency of Go Players: A Computational Approach Amr Ahmed Sabry Abdel-Rahman Ghoneim B.Sc. (Computer Science & Information Systems) Helwan University, Cairo - Egypt M.Sc. (Computer Science) Helwan University, Cairo - Egypt A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy at the School of Engineering & Information Technology the University of New South Wales at the Australian Defence Force Academy March 2012 ii [This Page is Intentionally Left Blank] iii Abstract Abstract Complex situations are very much context dependent, thus agents – whether human or artificial – need to attain an awareness based on their present situation. An essential part of that awareness is the accurate and effective perception and understanding of the set of knowledge, skills, and characteristics that are needed to allow an agent to perform a specific task with high performance, or what we would like to name, Competency Awareness. The development of this awareness is essential for any further development of an agent’s capabilities. This can be assisted by identifying the limitations in the so far developed expertise and consequently engaging in training processes that add the necessary knowledge to overcome those limitations. However, current approaches of competency and situation awareness rely on manual, lengthy, subjective, and intrusive techniques, rendering those approaches as extremely troublesome and ineffective when it comes to developing computerized agents within complex scenarios. Within the context of computer Go, which is currently a grand challenge to Artificial Intelligence, these issues have led to substantial bottlenecks that need to be addressed in order to achieve further improvements. Thus, the underlying principle of this work is that of the development of an automated, objective and non-intrusive methodology of Competency Assessment of decision-makers, which will practically aid in the understanding and provision of effective guidance to the development of improved decision-making capabilities, specifically within computer agents. In this study, we propose a framework whereby a computational environment is used to study and assess the competency of a decision maker. We use the game of GO to demonstrate this functionality in an environment in which hundreds of human-played GO games are analysed. In order to validate the proposed framework, a series of experiments on a wide range of problems have been conducted. These experiments automatically: (1) measure and monitor the competency of Human Go players, (2) reveal and monitor the dynamics of Neuro-Evolution, and (3) integrate strategic domain knowledge into evolutionary algorithms. The experimental results show that: (1) the iv Keywords proposed framework is effective in measuring and monitoring the strategic competencies of human Go players and evolved Go neuro-players, and (2) is effective in guiding the development of improved Go neuro-players when compared to traditional approaches that lacked the integration of a strategic competency measurement. Keywords Complex Scenarios, Decision Making, Strategic Reasoning, Competency Assessment, Situation Awareness, Situation Management, Skill Assessment, Computational Intelligence, Random Forests, Artificial Neural Networks, Evolutionary Computation, Neuro-Evolution, Rules Extraction, Network Motifs, Mind Games, Strategic Games, Board Games, Game Playing, Go, Computer Go v Graphical Abstract Graphical Abstract vi [This Page is Intentionally Left Blank] vii Acknowledgment Acknowledgment It would not have been possible to complete my PhD without the support of so many wonderful people. First of all, I would like to express my sincere thanks to my principal supervisor, Prof Hussein Abbass, for his wisdom and understanding, exchanging ideas, and his guidance in all aspects of my work, providing me great help on various topics. I also would like to express my sincere thanks to my co-supervisor, Dr Daryl Essam for his assistance and guidance, and particularly, his invaluable help with the game-of-Go side for this thesis. I would like to thank my dear colleagues and friends for helping me throughout my way; Theam Foo Ng, Essam Soliman, Saber El-Sayed, Noha Hamza, Ahmed Fathi, Abdelmonaem Fouad, Mai Shouman, Mohamed Mabrok, Mohammed Esmaeil-Zadeh, Eman Sayed, Irman Hermadi, Dominik Beck, Miriam Brandl, Gabriele Lo Tenero, Miriam Glennie, Farhana Naznin, Hafsa Ismail, Ibrahim Radwan, Andrew Asfaganov, Ahmed Thabet, Osama Hassanein, Yasmin Abdelraouf, Ahmed Samir, Ziyuan Li, Helen Gilory, Evgeny Mironov, Camille Pécastaings, Federica Salvetti, Sheila Tobing, Toby Boyson, Luis Espinosa, Bruno Barbosa, and my best mate Nizami Jafarov. I would also like to thank all my fellows in the Computational Intelligence, Modelling, and Cognition Lab. (CIMC). I particularly would like to deeply thank: Shir Li Wang, Wenjing Zhao, Van Viet Pham, Murad Hossain, Bing Wang, Heba El-Fiqi, George Leu, Kun (Liza) Wang, Sondoss El-Sawah, Shen Ren, Jiangjun Tang, Weicai Zhong, Sameer Alam, Bin Zhang, James Whitacre, Vinh Bui, Lam Bui, and Kamran Shafi. I am very grateful to Dr Sherene Suchy; her guidance, support and friendship have made it possible for me to achieve my potential. I am also grateful to many members of the school, who provided such a wonderful environment, especially, Ms Elvira Berra, Mrs Elizabeth Carey, Ms Christa Cordes, Mr Luke Garner, and Ms Mette Granvik. I am also very grateful to my many friends in Egypt, who proved to me how true friends can grow separately without growing apart. As always, you kept me going on guys!! Finally, for their tireless support and encouragement, I would like to thank my family – My Mom, Dad, sister Ghada, and brother Ayman – for providing me with their love and support throughout my PhD. viii [This Page is Intentionally Left Blank] ix Originality Statement Originality Statement I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged. Amr S. Ghoneim Signed ………….. Date …………….. x [This Page is Intentionally Left Blank] xi Copyright Statement Copyright Statement I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted. I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation. Amr S. Ghoneim Signed ………….. Date …………….. xii [This Page is Intentionally Left Blank] xiii List of Publications List of Publications Ghoneim, A. S., D. L. Essam, and H. A. Abbass (2011). Competency Awareness in Strategic Decision Making. In Proceedings of the IEEE First International Multi- Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), pp. 106–109, 22–24 Feb. 2011, Miami Beach, FL, USA. IEEE Press. Ghoneim, A. S., D. L. Essam, and H. A. Abbass (2011). On Computations and Strategies for Real and Artificial Systems. In Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems, edited by Tom Lenaerts, Mario Giacobini, Hugues Bersini, Paul Bourgine, Marco Dorigo and René Doursat, pp. 260–267, 8–12 August 2011, Paris, France. MIT Press. Ghoneim, A. S., and D. L. Essam (2012). A Methodology for Revealing and Monitoring the Strategies Played by Neural Networks in Mind Games. Accepted by the 2012 International Joint Conference on Neural Networks (IJCNN), at the 2012 IEEE World Congress on Computational Intelligence (WCCI 2012), Brisbane – Australia, June 10-15. xiv [This Page is Intentionally Left Blank] xv The Knowledge of anything, since all things have causes, is not acquired or complete unless it is known by its causes. --- Avicenna (980-1037) xvi Contents [This Page is Intentionally Left Blank] xvii Contents Contents Abstract ......................................................................................................................................... iii Keywords ....................................................................................................................................... iv Graphical Abstract ......................................................................................................................... v Acknowledgment ........................................................................................................................
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