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Othello

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* [[Mohd Nor Akmal Khalid]], [[E. Mei Ang]], [[Umi Kalsom Yusof]], [[Hiroyuki Iida]], [[Taichi Ishitobi]] ('''2015'''). ''[http://link.springer.com/chapter/10.1007%2F978-3-319-27947-3_6 Identifying Critical Positions Based on Conspiracy Numbers]''. [http://link.springer.com/book/10.1007/978-3-319-27947-3 Agents and Artificial Intelligence], [http://dblp.uni-trier.de/db/conf/icaart/icaart2015s.html#KhalidAYII15 ICAART 2015 - Revised Selected Papers]
* [[Shantanu Thakoor]], [[Surag Nair]], [[Megha Jhunjhunwala]] ('''2017'''). ''Learning to Play Othello Without Human Knowledge''. [[Stanford University]], [https://github.com/suragnair/alpha-zero-general/blob/master/pretrained_models/writeup.pdf pdf] » [[AlphaZero]], [[Monte-Carlo Tree Search|MCTS]], [[Deep Learning]] <ref>[https://github.com/suragnair/alpha-zero-general GitHub - suragnair/alpha-zero-general: A clean and simple implementation of a self-play learning algorithm based on AlphaGo Zero (any game, any framework!)]</ref>
* [[Paweł Liskowski]], [[Wojciech Jaśkowski]], [[Krzysztof Krawiec]] ('''2017'''). ''Learning to Play Othello with Deep Neural Networks''. [https://arxiv.org/abs/1711.06583 arXiv:1711.06583]<ref>[https://en.wikipedia.org/wiki/Edax_(computing) Edax] by [[Richard Delorme]]</ref>
* [[Paweł Liskowski]], [[Wojciech Jaśkowski]], [[Krzysztof Krawiec]] ('''2018'''). ''Learning to Play Othello with Deep Neural Networks''. [[IEEE#TOG|IEEE Transactions on Games]]
* [[Kiminori Matsuzaki]] ('''2018'''). ''Empirical Analysis of PUCT Algorithm with Evaluation Functions of Different Quality''. [[TAAI 2018]] » [[Christopher D. Rosin#PUCT|PUCT]]

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