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===ICGA Journal, Vol. 40, No. 3===
* [[Jos Uiterwijk]], ''Set Matching with applications: An enhancement of the Hales–Jewett pairing strategy''.
* [[Ching-Nung Lin]], [[Jr-Chang Chen]], [[Shi-Jim Yen]], [[Chan-San Chen]], ''Design of a Block Go program using deep learning and Monte Carlo tree search''. » [[Deep Learning]] [[Monte-Carlo Tree Search|MCTS]]
* [[Jaap van den Herik]], ''Computer chess: From idea to DeepMind''.
* [[Cameron Browne]], [[Todd W. Neller]], [[Jr-Chang Chen]], ''Computers and Games 2018''. » [[CG 2018]]
* [[Nelson Hernandez]], ''Choosing chess openings for TCEC10''. » [[TCEC Season 10]]
* [[Guy Haworth]], [[Nelson Hernandez]], ''TCEC11: the 11th Top Chess Engine Championship''. » [[TCEC Season 11]]
* [[Chao Gao]], [[Siqi Yan]], [[Ryan Hayward]], [[Martin Müller]], ''A transferable neural network for Hex''. » [[Hex]]
* [[François Bonnet]], ''Winning strategies in DarkHex: Hex with hidden stones''.
* [[Wei-Yuan Hsu]], [[Chu-Ling Ko]], [[Chu-Hsuan Hsueh]], [[I-Chen Wu]], ''Solving 7,7,5-game and 8,8,5-game''.
* [[Nathalie Chetcuti-Sperandio]], [[Fabien Delorme]], [[Sylvain Lagrue]], ''On aggregate and comparison functions for Motus/Lingo playing''.
* [[Zhang Song]], [[Hiroyuki Iida]], ''Using single conspiracy number for long term position evaluation''. » [[Conspiracy Numbers]]* [[Hung Guei]], [[Ting-Han Wei]], [[I-Chen Wu]], ''Using 2048-like games as a pedagogical tool for reinforcement learning''. » [[Reinforcement Learning]]
* [[Kiminori Matsuzaki]], [[Naoki Kitamura]], ''Do evaluation functions really improve Monte-Carlo tree search?'' » [[Othello]], [[Monte-Carlo Tree Search|MCTS]]
* [[Pham Hong Nguyen|Nguyen Hong Pham]], ''A completed implementation for Xiangqi rules''. » [[Chinese Chess|Xiangqi]]
* [[Xiali Li]], [[Song Wang]], [[Zhengyu Lv]], [[Yongji Li]], [[Licheng Wu]], ''Strategy research based on chess shapes for Tibetan JIU computer game''.
