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Othello

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* [[Toru Ueda]], [[Tsuyoshi Hashimoto]], [[Junichi Hashimoto]], [[Hiroyuki Iida]] ('''2008'''). ''[http://www.springerlink.com/content/v47864x734410148/ Weak Proof-Number Search]''. [[CG 2008]] » [[Proof-Number Search]]
* [[Marcin Szubert]], [[Wojciech Jaśkowski]], [[Krzysztof Krawiec]] ('''2009'''). ''Coevolutionary Temporal Difference Learning for Othello''. [[IEEE#CIG|IEEE Symposium on Computational Intelligence and Games]], [http://www.cs.put.poznan.pl/wjaskowski/pub/papers/szubert09coevolutionary.pdf pdf]
* [[Marcin Szubert]] ('''2009'''). ''Coevolutionary Reinforcement Learning and its Application to Othello''. M.Sc. thesis, [https://en.wikipedia.org/wiki/Pozna%C5%84_University_of_Technology Poznań University of Technology], supervisor [[Krzysztof Krawiec]], [https://mszubert.github.io/papers/Szubert_2009_MSC.pdf pdf]
==2010 ...==
* [[Edward P. Manning]] ('''2010'''). ''[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5409565 Using Resource-Limited Nash Memory to Improve an Othello Evaluation Function]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 2, No. 1
==2015 ...==
* [[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]
* [[Wojciech Jaśkowski]], [[Marcin Szubert]] ('''2016'''). ''[https://ieeexplore.ieee.org/document/7180338 Coevolutionary CMA-ES for Knowledge-Free Learning of Game Position Evaluation]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 8, No. 4
* [[Wojciech Jaśkowski]], [[Paweł Liskowski]], [[Marcin Szubert]], [[Krzysztof Krawiec]] ('''2016'''). ''[https://content.sciendo.com/view/journals/amcs/26/1/article-p215.xml The performance profile: A multi–criteria performance evaluation method for test–based problems]''. [https://en.wikipedia.org/wiki/International_Journal_of_Applied_Mathematics_and_Computer_Science International Journal of Applied Mathematics and Computer Science], Vol. 26, No. 1
* [[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]]
* [[Kiminori Matsuzaki]], [[Naoki Kitamura]] ('''2018'''). ''Do evaluation functions really improve Monte-Carlo tree search?'' [[CG 2018]], [[ICGA Journal#40_3|ICGA Journal, Vol. 40, No. 3]]

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