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Solving General Game Playing with Incomplete Information Problem Using Iterative Tree Search and Language Learning

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Solving General Game Playing with Incomplete Information Problem Using Iterative Tree Search and Language Learning Solving General Game Playing with Incomplete Information Problem using Iterative Tree Search and Language Learning Armin Chitizadeh Supervisor: Prof. Michael Thielscher Co-Supervisor: Dr. Alan David Blair A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy School of Computer Science and Engineering Faculty of Engineering December 2019 Thesis/Dissertation Sheet Surname/Family Name : Chitizadeh Given Name/s : Armin Abbreviation for degree as give in the University calendar : PhD Faculty : Engineering School : Computer Science and Engineering Solving General Game Playing with Incomplete Thesis Title : Information Problems using Iterative Tree Search and Language Learning Abstract General Game Playing with Incomplete Information (GGP-II) is about developing a system capable of successfully playing incomplete information games without human intervention by just receiving their rules at runtime. Different algorithms (players) have been provided to play games in GGP-II. This research is concerned with three main limitations of algorithms in the literature: valuing-information, generating mixed strategy and cooperating in games which require implicit communication. In this thesis, I theoretically and experimentally show why past GGP-II players suffer from these problems and introduce four algorithms to overcome these problems and discuss the advantages and limitations of each algorithm. Firstly, I introduce the Iterative Tree Search (ITS) algorithm. ITS learns the best strategy by simulating different plays with itself. I show theoretically and experimentally how ITS correctly values information and models opponents by generating mixed strategies in different games. However, ITS fails to play large games and also the cooperative games which require implicit communication. Secondly, I present the Monte Carlo Iterative Tree Search (MCITS). This algorithm uses Monte Carlo Tree Search technique to focus the search on a more promising part of the game. I experimentally show the success of this algorithm on different games from the literature. MCITS fails to generate mixed strategies and to correctly play games which require implicit communication. Thirdly, I introduce a communication language learning technique called General Language (GL). GL is capable of generating an implicit communication language for cooperative players to share their information. The GL technique sees a communication language as an additional game rule. It can be used on top of any existing GGP-II player. This feature makes it a general algorithm. The main limitation of GL is its inability to solve large problems. Finally, I present the General Language Tree Search algorithm (GLTS). This algorithm extends the GL technique to be applicable to large games. It prioritises the communication languages according to their closeness to the most successful one. To validate my claim, I perform an experiment using GLTS by providing it with a Multi-Agent Path Finding with Destination Uncertainty problem. The GLTS algorithm successfully discovers the desired strategies by utilising the implicit communication among agents. Declaration relating to disposition of project thesis/dissertation I hereby grant to the University of New South Wales or its agents a non-exclusive licence to archive and to make available (including to members of the public) my thesis or dissertation in whole or in part in the University libraries in all forms of media, now or here after known. I acknowledge that I retain all intellectual property rights which subsist in my thesis or dissertation, such as copyright and patent rights, subject to applicable law. I also retain the right to use all or part of my thesis or dissertation in future works (such as articles or books). …………………………………………………………… ……….……………………...…….… Signature Date The University recognises that there may be exceptional circumstances requiring restrictions on copying or conditions on use. Requests for restriction for a period of up to 2 years can be made when submitting the final copies of your thesis to the UNSW Library. Requests for a longer period of restriction may be considered in exceptional circumstances and require the approval of the Dean of Graduate Research. INCLUSION OF PUBLICATIONS STATEMENT UNSW is supportive of candidates publishing their research results during their candidature as detailed in the UNSW Thesis Examination Procedure. Publications can be used in their thesis in lieu of a Chapter if: • The candidate contributed greater than 50% of the content in the publication and is the “primary author”, ie. the candidate was responsible primarily for the planning, execution and preparation of the work for publication • The candidate has approval to include the publication in their thesis in lieu of a Chapter from their supervisor and Postgraduate Coordinator. • The publication is not subject to any obligations or contractual agreements with a third party that would constrain its inclusion in the thesis Please indicate whether this thesis contains published material or not: This thesis contains no publications, either published or submitted for publication ☐ (if this box is checked, you may delete all the material on page 2) Some of the work described in this thesis has been published and it has been ☒ documented in the relevant Chapters with acknowledgement (if this box is checked, you may delete all the material on page 2) This thesis has publications (either published or submitted for publication) ☐ incorporated into it in lieu of a chapter and the details are presented below CANDIDATE’S DECLARATION I declare that: • I have complied with the UNSW Thesis Examination Procedure • where I have used a publication in lieu of a Chapter, the listed publication(s) below meet(s) the requirements to be included in the thesis. Candidate’s Name Signature Date (dd/mm/yy) iv Originality Statement I hereby declare that this submission is my own work and to the best of my knowl- edge 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. Signed: ................................................... Date: ....................................................... v vi 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 also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstract International (this is applicable to doctoral theses only). 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. Signed: ................................................... Date: ....................................................... vii viii Authenticity Statement I certify that the Library deposit digital copy is a direct equivalent of the final officially approved version of my thesis. No emendation of content has occurred and if there are any minor variations in formatting, they are the result of the conversion to digital format. Signed: ................................................... Date: ....................................................... ix x Acknowledgements I wish to express my deepest gratitude to outstanding individuals who supported me to undertake this research, and it would not have been possible without their help. First and foremost, I wish to pay my special regards to my supervisor, Professor Michael Thielscher. It was his presentation on General Artificial Intelligence back in 2012 which made me interested in persuading the research. During my PhD, his guidance, support and ongoing encouragement were beyond the call of duty. Words are not enough to express to Michael how much it meant to me that he took the time to be such a caring mentor and improve my level of research, writing and critical thinking. Thank you. I would like to thank my parents, Jafar Chiti Zadeh, Nasrin Chitizadeh and my brother and sister, Amir Chiti Zadeh and Ayda Chitizadeh and my grandparents for their encouragement and support both mentally and financially throughout this research. I am so fortunate to have such a generous and understanding family who were always willing to talk and listen. Their continues encouragement and advice kept me moving at every step of this journey. I also wish to thank my co-supervisor, my panel, all the members of the GGP meeting group and my reviewers who helped me with their feedback and constructive criticism. xi Acknowledgements
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