Tomoyuki Kaneko

Publication Activity (10 Years)

Years Active: 2000-2023
Publications (10 Years): 33

Top Topics

Evaluation Function

Regret Minimization

Top Venues

Publications

Fanchao Xu, Tomoyuki Kaneko
Curiosity-driven Exploration for Cooperative Multi-Agent Reinforcement Learning. IJCNN (2023)
Shanchuan Wan, Yujin Tang, Yingtao Tian, Tomoyuki Kaneko
DEIR: Efficient and Robust Exploration through Discriminative-Model-Based Episodic Intrinsic Rewards. IJCAI (2023)
Shanchuan Wan, Yujin Tang, Yingtao Tian, Tomoyuki Kaneko
DEIR: Efficient and Robust Exploration through Discriminative-Model-Based Episodic Intrinsic Rewards. CoRR (2023)
Chen Chen, Tomoyuki Kaneko
Learning Strategies for Imperfect Information Board Games Using Depth-Limited Counterfactual Regret Minimization and Belief State. CoG (2022)
Taichi Nakayashiki, Tomoyuki Kaneko
Maximum Entropy Reinforcement Learning in Two-Player Perfect Information Games. SSCI (2021)
Hanhua Zhu, Tomoyuki Kaneko
Residual Network for Deep Reinforcement Learning with Attention Mechanism. J. Inf. Sci. Eng. 37 (3) (2021)
Zhejie Hu, Tomoyuki Kaneko
Hierarchical Advantage for Reinforcement Learning in Parameterized Action Space. CoG (2021)
Cheng Yi, Tomoyuki Kaneko
Improving Counterfactual Regret Minimization Agents Training in Card Game Cheat Using Ordered Abstraction. ACG (2021)
Fanchao Xu, Tomoyuki Kaneko
Local Coordination in Multi-Agent Reinforcement Learning. TAAI (2021)
Quentin Gendre, Tomoyuki Kaneko
Playing Catan with Cross-dimensional Neural Network. CoRR (2020)
Yuji Kanagawa, Tomoyuki Kaneko
Diverse Exploration via InfoMax Options. CoRR (2020)
Quentin Gendre, Tomoyuki Kaneko
Playing Catan with Cross-Dimensional Neural Network. ICONIP (2) (2020)
Taichi Nakayashiki, Tomoyuki Kaneko
Evaluation of Loss Function for Stable Policy Learning in Dobutsu Shogi. TAAI (2020)
Zhejie Hu, Tomoyuki Kaneko
Application of Deep-RL with Sample-Efficient Method in Mini-games of StarCraft II. TAAI (2019)
Yuji Kanagawa, Tomoyuki Kaneko
Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning. CoRR (2019)
Chen Chen, Tomoyuki Kaneko
Acquiring Strategies for the Board Game Geister by Regret Minimization. TAAI (2019)
Yuji Kanagawa, Tomoyuki Kaneko
Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning. CoG (2019)
Tomoyuki Kaneko, Takenobu Takizawa
Computer Shogi Tournaments and Techniques. IEEE Trans. Games 11 (3) (2019)
Yusaku Mandai, Tomoyuki Kaneko
RankNet for evaluation functions of the game of Go. J. Int. Comput. Games Assoc. 41 (2) (2019)
Hanhua Zhu, Tomoyuki Kaneko
Deep Residual Attention Reinforcement Learning. TAAI (2019)
Tianhe Wang, Tomoyuki Kaneko
Application of Deep Reinforcement Learning in Werewolf Game Agents. TAAI (2018)
Taichi Nakayashiki, Tomoyuki Kaneko
Learning of Evaluation Functions via Self-Play Enhanced by Checkmate Search. TAAI (2018)
Hyunwoo Oh, Tomoyuki Kaneko
Deep Recurrent Q-Network with Truncated History. TAAI (2018)
Hanhua Zhu, Tomoyuki Kaneko
Comparison of Loss Functions for Training of Deep Neural Networks in Shogi. TAAI (2018)
Yusaku Mandai, Tomoyuki Kaneko
Alternative Multitask Training for Evaluation Functions in Game of Go. TAAI (2018)
Shanchuan Wan, Tomoyuki Kaneko
Heterogeneous Multi-task Learning of Evaluation Functions for Chess and Shogi. ICONIP (3) (2018)
Shanchuan Wan, Tomoyuki Kaneko
Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks. CIG (2018)
Shanchuan Wan, Tomoyuki Kaneko
Imitation Learning for Playing Shogi Based on Generative Adversarial Networks. TAAI (2017)
Takahisa Imagawa, Tomoyuki Kaneko
Estimating the Maximum Expected Value through Upper Confidence Bound of Likelihood. TAAI (2017)
Yusaku Mandai, Tomoyuki Kaneko
LinUCB applied to Monte Carlo tree search. Theor. Comput. Sci. 644 (2016)
Yusaku Mandai, Tomoyuki Kaneko
Improved LinUCT and its evaluation on incremental random-feature tree. CIG (2016)
Takahisa Imagawa, Tomoyuki Kaneko
Monte Carlo Tree Search with Robust Exploration. Computers and Games (2016)
Shotaro Omori, Tomoyuki Kaneko
Learning of Evaluation Functions to Realize Playing Styles in Shogi. PRICAI (2016)
Takahisa Imagawa, Tomoyuki Kaneko
Enhancements in Monte Carlo tree search algorithms for biased game trees. CIG (2015)
Yusaku Mandai, Tomoyuki Kaneko
LinUCB Applied to Monte-Carlo Tree Search. ACG (2015)
Shogo Takeuchi, Tomoyuki Kaneko
Estimating Ratings of Computer Players by the Evaluation Scores and Principal Variations in Shogi. ACIT-CSI (2015)
Shu Yokoyama, Tomoyuki Kaneko, Tetsuro Tanaka
Parameter-Free Tree Style Pipeline in Asynchronous Parallel Game-Tree Search. ACG (2015)
Kunihito Hoki, Tomoyuki Kaneko
Large-Scale Optimization for Evaluation Functions with Minimax Search. J. Artif. Intell. Res. 49 (2014)
Kunihito Hoki, Tomoyuki Kaneko, Akihiro Kishimoto, Takeshi Ito
Parallel Dovetailing and its Application to Depth-First Proof-Number Search. J. Int. Comput. Games Assoc. 36 (1) (2013)
Hiroyuki Hamada, Fumimasa Nomura, Tomoyuki Kaneko, Kenji Yasuda, Masahiro Okamoto
Exploring the implicit interlayer regulatory mechanism between cells and tissue: Stochastic mathematical analyses of the spontaneous ordering in beating synchronization. Biosyst. 111 (3) (2013)
Kunihito Hoki, Tomoyuki Kaneko, Daisaku Yokoyama, Takuya Obata, Hiroshi Yamashita, Yoshimasa Tsuruoka, Takeshi Ito
A System-Design Outline of the Distributed-Shogi-System Akara 2010. SNPD (2013)
Yoshiaki Yamaguchi, Kazunori Yamaguchi, Tetsuro Tanaka, Tomoyuki Kaneko
Infinite Connect-Four Is Solved: Draw. ACG (2011)
Kazuki Yoshizoe, Akihiro Kishimoto, Tomoyuki Kaneko, Haruhiro Yoshimoto, Yutaka Ishikawa
Scalable Distributed Monte-Carlo Tree Search. SOCS (2011)
Tomoyuki Kaneko, Kunihito Hoki
Analysis of Evaluation-Function Learning by Comparison of Sibling Nodes. ACG (2011)
Kunihito Hoki, Tomoyuki Kaneko
The Global Landscape of Objective Functions for the Optimization of Shogi Piece Values with a Game-Tree Search. ACG (2011)
Tomoyuki Kaneko
Parallel Depth First Proof Number Search. AAAI (2010)
Shogo Takeuchi, Tomoyuki Kaneko, Kazunori Yamaguchi
Evaluation of Game Tree Search Methods by Game Records. IEEE Trans. Comput. Intell. AI Games 2 (4) (2010)
Shogo Takeuchi, Tomoyuki Kaneko, Kazunori Yamaguchi
Evaluation of Monte Carlo tree search and the application to Go. CIG (2008)
Shogo Takeuchi, Tomoyuki Kaneko, Kazunori Yamaguchi, Satoru Kawai
Visualization and Adjustment of Evaluation Functions Based on Evaluation Values and Win Probability. AAAI (2007)
Shunsuke Soeda, Tomoyuki Kaneko, Tetsuro Tanaka
Dual Lambda Search and Shogi Endgames. ACG (2006)
Haruhiro Yoshimoto, Kazuki Yoshizoe, Tomoyuki Kaneko, Akihiro Kishimoto, Kenjiro Taura
Monte Carlo Go Has a Way to Go. AAAI (2006)
Tomoyuki Kaneko, Kazunori Yamaguchi, Satoru Kawai
Automated Identification of Patterns in Evaluation Functions. ACG (2003)
Tomoyuki Kaneko, Kazunori Yamaguchi, Satoru Kawai
Compiling Logical Features into Specialized State-Evaluators by Partial Evaluation, Boolean Tables and Incremental Calculation. PRICAI (2000)