Tomoyuki Kaneko

Orcid: 0000-0001-8051-2388

According to our database1, Tomoyuki Kaneko authored at least 49 papers between 2000 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2023
Curiosity-driven Exploration for Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the International Joint Conference on Neural Networks, 2023

DEIR: Efficient and Robust Exploration through Discriminative-Model-Based Episodic Intrinsic Rewards.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022
Learning Strategies for Imperfect Information Board Games Using Depth-Limited Counterfactual Regret Minimization and Belief State.
Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

2021
Residual Network for Deep Reinforcement Learning with Attention Mechanism.
J. Inf. Sci. Eng., 2021

Local Coordination in Multi-Agent Reinforcement Learning.
Proceedings of the 2021 International Conference on Technologies and Applications of Artificial Intelligence, 2021

Maximum Entropy Reinforcement Learning in Two-Player Perfect Information Games.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Hierarchical Advantage for Reinforcement Learning in Parameterized Action Space.
Proceedings of the 2021 IEEE Conference on Games (CoG), 2021

Improving Counterfactual Regret Minimization Agents Training in Card Game Cheat Using Ordered Abstraction.
Proceedings of the Advances in Computer Games - 17th International Conference, 2021

2020
Diverse Exploration via InfoMax Options.
CoRR, 2020

Evaluation of Loss Function for Stable Policy Learning in Dobutsu Shogi.
Proceedings of the International Conference on Technologies and Applications of Artificial Intelligence, 2020

Playing Catan with Cross-Dimensional Neural Network.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

2019
Computer Shogi Tournaments and Techniques.
IEEE Trans. Games, 2019

RankNet for evaluation functions of the game of Go.
J. Int. Comput. Games Assoc., 2019

Deep Residual Attention Reinforcement Learning.
Proceedings of the 2019 International Conference on Technologies and Applications of Artificial Intelligence, 2019

Application of Deep-RL with Sample-Efficient Method in Mini-games of StarCraft II.
Proceedings of the 2019 International Conference on Technologies and Applications of Artificial Intelligence, 2019

Acquiring Strategies for the Board Game Geister by Regret Minimization.
Proceedings of the 2019 International Conference on Technologies and Applications of Artificial Intelligence, 2019

Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning.
Proceedings of the IEEE Conference on Games, 2019

2018
Comparison of Loss Functions for Training of Deep Neural Networks in Shogi.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2018

Application of Deep Reinforcement Learning in Werewolf Game Agents.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2018

Deep Recurrent Q-Network with Truncated History.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2018

Learning of Evaluation Functions via Self-Play Enhanced by Checkmate Search.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2018

Alternative Multitask Training for Evaluation Functions in Game of Go.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2018

Heterogeneous Multi-task Learning of Evaluation Functions for Chess and Shogi.
Proceedings of the Neural Information Processing - 25th International Conference, 2018

Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks.
Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games, 2018

2017
Imitation Learning for Playing Shogi Based on Generative Adversarial Networks.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2017

Estimating the Maximum Expected Value through Upper Confidence Bound of Likelihood.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2017

2016
LinUCB applied to Monte Carlo tree search.
Theor. Comput. Sci., 2016

Learning of Evaluation Functions to Realize Playing Styles in Shogi.
Proceedings of the PRICAI 2016: Trends in Artificial Intelligence, 2016

Improved LinUCT and its evaluation on incremental random-feature tree.
Proceedings of the IEEE Conference on Computational Intelligence and Games, 2016

Monte Carlo Tree Search with Robust Exploration.
Proceedings of the Computers and Games - 9th International Conference, 2016

2015
Enhancements in Monte Carlo tree search algorithms for biased game trees.
Proceedings of the 2015 IEEE Conference on Computational Intelligence and Games, 2015

Estimating Ratings of Computer Players by the Evaluation Scores and Principal Variations in Shogi.
Proceedings of the 3rd International Conference on Applied Computing and Information Technology, 2015

Parameter-Free Tree Style Pipeline in Asynchronous Parallel Game-Tree Search.
Proceedings of the Advances in Computer Games - 14th International Conference, 2015

2014
Large-Scale Optimization for Evaluation Functions with Minimax Search.
J. Artif. Intell. Res., 2014

2013
Parallel Dovetailing and its Application to Depth-First Proof-Number Search.
J. Int. Comput. Games Assoc., 2013

Exploring the implicit interlayer regulatory mechanism between cells and tissue: Stochastic mathematical analyses of the spontaneous ordering in beating synchronization.
Biosyst., 2013

A System-Design Outline of the Distributed-Shogi-System Akara 2010.
Proceedings of the 14th ACIS International Conference on Software Engineering, 2013

2011
Scalable Distributed Monte-Carlo Tree Search.
Proceedings of the Fourth Annual Symposium on Combinatorial Search, 2011

Infinite Connect-Four Is Solved: Draw.
Proceedings of the Advances in Computer Games - 13th International Conference, 2011

Analysis of Evaluation-Function Learning by Comparison of Sibling Nodes.
Proceedings of the Advances in Computer Games - 13th International Conference, 2011

The Global Landscape of Objective Functions for the Optimization of Shogi Piece Values with a Game-Tree Search.
Proceedings of the Advances in Computer Games - 13th International Conference, 2011

2010
Evaluation of Game Tree Search Methods by Game Records.
IEEE Trans. Comput. Intell. AI Games, 2010

Parallel Depth First Proof Number Search.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2008
Evaluation of Monte Carlo tree search and the application to Go.
Proceedings of the 2008 IEEE Symposium on Computational Intelligence and Games, 2008

2007
Visualization and Adjustment of Evaluation Functions Based on Evaluation Values and Win Probability.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Dual Lambda Search and Shogi Endgames.
Proceedings of the Advances in Computer Games, 11th International Conference, 2006

Monte Carlo Go Has a Way to Go.
Proceedings of the Proceedings, 2006

2003
Automated Identification of Patterns in Evaluation Functions.
Proceedings of the Advances in Computer Games, 2003

2000
Compiling Logical Features into Specialized State-Evaluators by Partial Evaluation, Boolean Tables and Incremental Calculation.
Proceedings of the PRICAI 2000, Topics in Artificial Intelligence, 6th Pacific Rim International Conference on Artificial Intelligence, Melbourne, Australia, August 28, 2000


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