Strength Improvement and Analysis for an MCTS-Based Chinese Dark Chess Program. - Chu-Hsuan Hsueh; I-Chen Wu; Wen-Jie Tseng 001; Shi-Jim Yen; Jr-Chang Chen (ACG, 2015)

Belief-state Monte-Carlo tree search for Phantom games. - Jiao Wang 005; Tan Zhu; Hongye Li; Chu-Hsuan Hsueh; I-Chen Wu (CIG, 2015)

Applying hueristic algorithms to portfolio selection problem. - Po-Ya Kang; I-Chen Wu; Chu-Hsuan Hsueh (TAAI, 2015)

DARKKNIGHT wins Chinese Dark Chess Tournament. - Chu-Hsuan Hsueh; I-Chen Wu (J. Int. Comput. Games Assoc., 2015)

Multi-Stage Temporal Difference Learning for 2048-like Games. - Kun-Hao Yeh; I-Chen Wu; Chu-Hsuan Hsueh; Chia-Chuan Chang; Chao-Chin Liang; Han Chiang (CoRR, 2016)

An analysis for strength improvement of an MCTS-based program playing Chinese dark chess. - Chu-Hsuan Hsueh; I-Chen Wu; Wen-Jie Tseng 001; Shi-Jim Yen; Jr-Chang Chen (Theor. Comput. Sci., 2016)

An Agent for EinStein Würfelt Nicht! Using N-Tuple Networks. - Yeong-Jia Roger Chu; Yuan-Hao Chen; Chu-Hsuan Hsueh; I-Chen Wu (TAAI, 2017)

Only-One-Victor Pattern Learning in Computer Go. - Jiao Wang 005; Chenjun Xiao; Tan Zhu; Chu-Hsuan Hsueh; Wen-Jie Tseng 001; I-Chen Wu (IEEE Trans. Comput. Intell. AI Games, 2017)

Multistage Temporal Difference Learning for 2048-Like Games. - Kun-Hao Yeh; I-Chen Wu; Chu-Hsuan Hsueh; Chia-Chuan Chang; Chao-Chin Liang; Han Chiang (IEEE Trans. Comput. Intell. AI Games, 2017)

AlphaZero for a Non-Deterministic Game. - Chu-Hsuan Hsueh; I-Chen Wu; Jr-Chang Chen; Tsan-sheng Hsu (TAAI, 2018)

Solving 7, 7, 5-game and 8, 8, 5-game. - Wei-Yuan Hsu; Chu-Ling Ko; Chu-Hsuan Hsueh; I-Chen Wu (J. Int. Comput. Games Assoc., 2018)

An investigation of strength analysis metrics for game-playing programs: A case study in Chinese dark chess. - Chu-Hsuan Hsueh; I-Chen Wu; Tsan-sheng Hsu; Jr-Chang Chen (J. Int. Comput. Games Assoc., 2018)

Belief-State Monte Carlo Tree Search for Phantom Go. - Jiao Wang 005; Tan Zhu; Hongye Li; Chu-Hsuan Hsueh; I-Chen Wu (IEEE Trans. Games, 2018)

Improving Human Players' T-Spin Skills in Tetris with Procedural Problem Generation. - Taishi Oikawa; Chu-Hsuan Hsueh; Kokolo Ikeda (ACG, 2019)

Combining Deep Deterministic Policy Gradient with Cross-Entropy Method. - Tung-Yi Lai; Chu-Hsuan Hsueh; You-Hsuan Lin; Yeong-Jia Roger Chu; Bo Yang Hsueh; I-Chen Wu (TAAI, 2019)

EWIN wins EinStein Würfelt Nicht! tournament. - Chu-Hsuan Hsueh; I-Chen Wu (J. Int. Comput. Games Assoc., 2019)

Imitating Agents in A Complex Environment by Generative Adversarial Imitation Learning. - Wanxiang Li; Chu-Hsuan Hsueh; Kokolo Ikeda (CoG, 2020)

Analyses of Tabular AlphaZero on NoGo. - Chu-Hsuan Hsueh; Kokolo Ikeda; Sang-Gyu Nam; I-Chen Wu (TAAI, 2020)

On solving the 7, 7, 5-game and the 8, 8, 5-game. - Wei-Yuan Hsu; Chu-Ling Ko; Jr-Chang Chen; Ting-Han Wei; Chu-Hsuan Hsueh; I-Chen Wu (Theor. Comput. Sci., 2020)

Procedural Maze Generation Considering Difficulty from Human Players' Perspectives. - Keita Fujihira; Chu-Hsuan Hsueh; Kokolo Ikeda (ACG, 2021)

Position Control and Production of Various Strategies for Game of Go Using Deep Learning Methods. - Yuan Shi; Tianwen Fan; Wanxiang Li; Chu-Hsuan Hsueh; Kokolo Ikeda (J. Inf. Sci. Eng., 2021)

Playing Good-Quality Games with Weak Players by Combining Programs with Different Roles. - Chu-Hsuan Hsueh; Kokolo Ikeda (CoG, 2022)

Graph Convolutional Networks for Turn-Based Strategy Games. - Wanxiang Li; Houkuan He; Chu-Hsuan Hsueh; Kokolo Ikeda (ICAART (2), 2022)

CLAP_CDC wins Chinese dark chess tournament. - Chu-Hsuan Hsueh; Jr-Chang Chen (J. Int. Comput. Games Assoc., 2022)

Generation of Game Stages With Quality and Diversity by Reinforcement Learning in Turn-Based RPG. - Sang-Gyu Nam; Chu-Hsuan Hsueh; Kokolo Ikeda (IEEE Trans. Games, 2022)

Can We Infer Move Sequences in Go from Stone Arrangements? - Chu-Hsuan Hsueh; Kokolo Ikeda (ACG, 2023)

Improving the Human-Likeness of Game AI's Moves by Combining Multiple Prediction Models. - Tatsuyoshi Ogawa; Chu-Hsuan Hsueh; Kokolo Ikeda (ICAART (3), 2023)

Procedural Content Generation of Super Mario Levels Considering Natural Connection. - SangGyu Nam; Chu-Hsuan Hsueh; Kokolo Ikeda (JCSSE, 2023)

Factor Analyses on Positive and Negative Evaluations of Games against Go Programs. - Kyota Kuboki; Chu-Hsuan Hsueh; Kokolo Ikeda (TAAI (1), 2023)

An Empirical Analysis of Gumbel MuZero on Stochastic and Deterministic Einstein Würfelt Nicht! - Chien-Liang Kuo; Po-Ting Chen; Hung Guei; De-Rong Sung; Chu-Hsuan Hsueh; Ti-Rong Wu; I-Chen Wu (TAAI (1), 2023)

Analyses of Tabular AlphaZero on Strongly-Solved Stochastic Games. - Chu-Hsuan Hsueh; Kokolo Ikeda; I-Chen Wu; Jr-Chang Chen; Tsan-sheng Hsu (IEEE Access, 2023)

Advances in Computer Games (ACG 2023) conference report. - Michael Hartisch; Chu-Hsuan Hsueh; Jonathan Schaeffer 001 (J. Int. Comput. Games Assoc., 2023)

Improvement of move naturalness for playing good-quality games with middle-level players. - Chu-Hsuan Hsueh; Kokolo Ikeda (Appl. Intell., 2024)

Using Reinforcement Learning to Generate Levels of Super Mario Bros. With Quality and Diversity. - SangGyu Nam; Chu-Hsuan Hsueh; Pavinee Rerkjirattikal; Kokolo Ikeda (IEEE Trans. Games, 2024)

More Human-Like Gameplay by Blending Policies From Supervised and Reinforcement Learning. - Tatsuyoshi Ogawa; Chu-Hsuan Hsueh; Kokolo Ikeda (IEEE Trans. Games, 2024)

Proposal and generation of endgame puzzles for an imperfect information game Geister. - Chu-Hsuan Hsueh; Takefumi Ishii; Tsuyoshi Hashimoto; Kokolo Ikeda (Entertain. Comput., 2025)

Policies of Multiple Skill Levels for Better Strength Estimation in Games. - Kyota Kuboki; Tatsuyoshi Ogawa; Chu-Hsuan Hsueh; Shi-Jim Yen; Kokolo Ikeda (CoRR, 2025)