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助研究員  |  吳廸融  
 
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Publications
 
Journal Articles
 
1. Chung-Chin Shih, Ting Han Wei, Ti-Rong Wu, I-Chen Wu, "A Local-Pattern Related Look-Up Table," to appear in IEEE Transactions on Games.
2. 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, August 2020.
3. 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, December 2018.
 
 
Conference Papers
 
1. Chien-Liang Kuo, Po-Ting Chen, Hung Guei, De-Rong Sung, Chu-Hsuan Hsueh, Ti-Rong Wu, I-Chen Wu, "An Empirical Analysis of Gumbel MuZero on Stochastic and Deterministic Einstein Würfelt Nicht!," the 28th International Conference on Technologies and Applications of Artificial Intelligence (TAAI), December 2023.
2. Ti-Rong Wu, Hung Guei, Ting Han Wei, Chung-Chin Shih, Jui-Te Chin, I-Chen Wu, "Game Solving with Online Fine-Tuning," The Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), December 2023, (Acceptance rate: 26.1% (3,218/12,343))
3. 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), December 2022.
4. 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?," the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), November 2022, (Acceptance rate: 25.6% (2,672/10,411))
5. 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," the Tenth International Conference on Learning Representations (ICLR), April 2022, (Acceptance rate: 32.3% (1,095/3,391))
6. 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), volume 36, number 9, February 2022, (Acceptance rate: 15.0% (1,349/9,020))
7. 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), volume 35, pages 259–267, February 2021, (Acceptance rate: 21.4% (1,692/7,911))
8. 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), volume 34, pages 1046–1053, February 2020, (Acceptance rate: 20.6% (1,591/7,737), Oral presentation: 5.85% (453/7,737))
9. Hsiao-Chung Hsieh, Ti-Rong Wu, Ting-Han Wei, I-Chen Wu, "Net2Net Extension for the Alphago Zero Algorithm," Advances in Computer Games (ACG), volume 12516, pages 131–142, August 2019.
10. 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), volume 33, pages 1222–1229, January 2019, (Acceptance rate: 16.2% (1,150/7,095))
 
 
 
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