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Applications of Artificial Intelligence and Machine Learning in Othello

Applications of Artificial Intelligence and Machine Learning in Othello. Jack Chen TJHSST Computer Systems Lab 2009-2010. Abstract.

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Applications of Artificial Intelligence and Machine Learning in Othello

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  1. Applications of Artificial Intelligence and Machine Learning in Othello Jack Chen TJHSST Computer Systems Lab 2009-2010

  2. Abstract The purpose of this project is to explore Artificial Intelligence techniques in the board game Othello. The project focuses on the creation and evaluation of AI players for Othello. It explores several techniques used in strong AI players, including improvements to minimax game-tree search algorithms and higher-quality evaluation functions. It also investigates machine learning methods to enable AI players to improve the quality and speed of play automatically based on training and experience.

  3. Scope of Study • Referee • GUI • AI players • Search algorithms • Board evaluation functions • Machine learning

  4. Referee • Written in Python • Supports varying types of players • AI programs in multiple languages • Humans • Runs the players in child processes • Can display board in a GUI

  5. GUI • Written in C++ • Qt graphics toolkit • Displays board • Animates players' moves • Allows human to play easily

  6. Search Algorithms • Minimax • Alpha-beta pruning • NegaScout • MTD(f) • Selective search • Quiescence search

  7. Board Evaluation Function • Complex features: mobility, stability • Simple features: patterns of disks • Training with machine learning • Stochastic gradient descent • Genetic algorithms • Neural networks, backpropogation

  8. Other AI enhancements • Bitboards • Transposition tables • Opening book • Parallelization

  9. Expected Results • Evaluate players based on performance in games against other players • Compare several different AIs • Players using machine learning would be expected to improve

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