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| Publications |
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| Journal Articles | | |
| 1. |
An-Jen Liu, Ti-Rong Wu, I-Chen Wu, Hung Guei, Ting-han Wei, "Strength Adjustment and Assessment for MCTS-Based Programs," IEEE Computational Intelligence Magazine, volume 15(3), pages 60–73, July 2020. |
| 2. |
Ti-Rong Wu, I-Chen Wu, Guan-Wun Chen, Ting-han Wei, Hung-Chun Wu, Tung-Yi Lai, Li-Cheng Lan, "Multilabeled Value Networks for Computer Go," IEEE Transactions on Games, volume 10(4), pages 378–389, July 2018. |
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| Conference Papers | | |
| 1. |
Chih-Yu Kao, Hung Guei, Ti-Rong Wu, I-Chen Wu, "Gumbel MuZero for the Game of 2048," The 27th International Conference on Technologies and Applications of Artificial Intelligence (TAAI 2022), December 2022. |
| 2. |
Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh, "Are AlphaZero-like Agents Robust to Adversarial Perturbations?," Conference on Neural Information Processing Systems (NeurIPS 2022), November 2022, (Acceptance rate: 25.6% (2,672/10,411)) |
| 3. |
Ti-Rong Wu, Chung-Chin Shih, Ting Han Wei, Meng-Yu Tsai, Wei-Yuan Hsu, I-Chen Wu, "AlphaZero-based Proof Cost Network to Aid Game Solving," International Conference on Learning Representations (ICLR 2022), April 2022, (Acceptance rate: 32.3% (1,095/3,391)) |
| 4. |
Chung-Chin Shih, Ti-Rong Wu, Ting Han Wei, I-Chen Wu, "A Novel Approach to Solving Goal-Achieving Problems for Board Games," The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), volume 36, number 9, February 2022, (Acceptance rate: 15.0% (1,349/9,020)) |
| 5. |
Li-Cheng Lan, Ti-Rong Wu, I-Chen Wu, Cho-Jui Hsieh, "Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search," The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), volume 35, pages 259–267, February 2021, (Acceptance rate: 21.4% (1,692/7,911)) |
| 6. |
Ti-Rong Wu, Ting-Han Wei, I-Chen Wu, "Accelerating and Improving Alphazero Using Population Based Training," The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), volume 34, pages 1046–1053, February 2020, (Acceptance rate: 20.6% (1,591/7,737), Oral presentation: 5.85% (453/7,737)) |
| 7. |
Hsiao-Chung Hsieh, Ti-Rong Wu, Ting-Han Wei, I-Chen Wu, "Net2Net Extension for the Alphago Zero Algorithm," Advances in Computer Games, volume 12516, pages 131–142, August 2019. |
| 8. |
I-Chen Wu, Ti-Rong Wu, An-Jen Liu, Hung Guei, Tinghan Wei, "On Strength Adjustment for MCTS-Based Programs," The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), volume 33, pages 1222–1229, January 2019, (Acceptance rate: 16.2% (1,150/7,095)) |
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