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[1] János Wágner,et al. Solving Renju , 2001, J. Int. Comput. Games Assoc..
[2] P. Alam,et al. H , 1887, High Explosives, Propellants, Pyrotechnics.
[3] Jonathan Schaeffer,et al. Checkers Is Solved , 2007, Science.
[4] H. Jaap van den Herik,et al. Proof-Number Search , 1994, Artif. Intell..
[5] Mark H. M. Winands,et al. 6 x 6 LOA is Solved , 2008 .
[6] S. Hewitt,et al. 2008 , 2018, Los 25 años de la OMC: Una retrospectiva fotográfica.
[7] Akihiro Kishimoto,et al. Parallel Dovetailing and its Application to Depth-First Proof-Number Search , 2013, J. Int. Comput. Games Assoc..
[8] H. Jaap van den Herik,et al. Best Play in Fanorona Leads to Draw , 2008 .
[9] Mark H. M. Winands,et al. Monte-Carlo Tree Search Solver , 2008, Computers and Games.
[10] Nils J. Nilsson,et al. Artificial Intelligence , 1974, IFIP Congress.
[11] H. Jaap van den Herik,et al. Games solved: Now and in the future , 2002, Artif. Intell..
[12] David Silver,et al. Monte-Carlo tree search and rapid action value estimation in computer Go , 2011, Artif. Intell..
[13] R. Lathe. Phd by thesis , 1988, Nature.
[14] Tristan Cazenave,et al. Developments on Product Propagation , 2013, Computers and Games.
[15] Jakub Pawlewicz,et al. Scalable Parallel DFPN Search , 2013, Computers and Games.
[16] Chiara Federica Sironi,et al. Monte-Carlo Tree Search for Artificial General Intelligence in Games , 2019 .
[17] Nicolas Jouandeau,et al. Solving breakthrough with Race Patterns and Job-Level Proof Number Search , 2011, ACG.
[18] Jos W. H. M. Uiterwijk. 11 x 11 Domineering is Solved: The first player wins , 2016, ArXiv.
[19] Mark H. M. Winands,et al. Solving Go for Rectangular Boards , 2009, J. Int. Comput. Games Assoc..
[20] Michael I. Jordan,et al. Advances in Neural Information Processing Systems 30 , 1995 .
[21] Thorsten von Eicken,et al. 技術解説 IEEE Computer , 1999 .
[22] Mark H. M. Winands. 6×6 LOA is Solved , 2008, J. Int. Comput. Games Assoc..
[23] Hiroyuki Iida,et al. Application of the killer-tree heuristic and the lambda-search method to lines of action , 2003, Inf. Sci..
[24] Akihiro Kishimoto,et al. Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning , 2019, NeurIPS.
[25] Chao Gao,et al. Focused Depth-first Proof Number Search using Convolutional Neural Networks for the Game of Hex , 2017, IJCAI.
[26] Jos W. H. M. Uiterwijk,et al. 11 \times 11 Domineering Is Solved: The First Player Wins , 2016, Computers and Games.
[27] D. M. Breuker. Memory versus search in games , 1998 .
[28] C. Scott,et al. IEEE Transactions on Pattern Analysis and Machine Intelligence , 2009 .
[29] H. Jaap van den Herik,et al. GO‐MOKU SOLVED BY NEW SEARCH TECHNIQUES , 1996, Comput. Intell..
[30] Hiroyuki Iida,et al. A comparative study of solvers in Amazons endgames , 2008, 2008 IEEE Symposium On Computational Intelligence and Games.
[31] Martin Müller,et al. Fuego—An Open-Source Framework for Board Games and Go Engine Based on Monte Carlo Tree Search , 2010, IEEE Transactions on Computational Intelligence and AI in Games.
[32] Jonathan Schaeffer,et al. The History Heuristic and Alpha-Beta Search Enhancements in Practice , 1989, IEEE Trans. Pattern Anal. Mach. Intell..
[33] A. Nagai. Df-pn Algorithm for Searching AND/OR Trees and Its Applications , 2002 .
[34] Dennis J. N. J. Soemers,et al. A Practical Introduction to the Ludii General Game System , 2019, ACG.
[35] Henri E. Bal,et al. Solving awari with parallel retrograde analysis , 2003, Computer.
[36] Tristan Cazenave,et al. Score Bounded Monte-Carlo Tree Search , 2010, Computers and Games.
[37] Demis Hassabis,et al. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play , 2018, Science.
[38] Olivier Teytaud,et al. Revisiting Monte-Carlo Tree Search on a Normal Form Game: NoGo , 2011, EvoApplications.
[39] Tristan Cazenave,et al. Generalized Rapid Action Value Estimation , 2015, IJCAI.
[40] Tristan Cazenave,et al. Playout policy adaptation with move features , 2016, Theor. Comput. Sci..
[41] L. Christophorou. Science , 2018, Emerging Dynamics: Science, Energy, Society and Values.