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\n\u6700\u9ad8\u5b78\u6b77<\/b>\uff1aPh.D. in Computer Science, Carnegie Mellon University, Pittsburgh, August 1993.
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\n \n\u671f\u520a\u8ad6\u6587<\/th>\n<\/tr>\n<\/tbody>\n \n [1]<\/td>\n Eileen Wong, Chih-Wei Tsai, Wenbo Gu, Pai-Lien Chen, Lydia Leung, I-Chen Wu, P. Strohl, Rodney J. Folz, Wail Yar, Ambrose A. Chiang, “Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire”, PLOS ONE, October 11, 2021.<\/td>\n<\/tr>\n \n [2]<\/td>\n Hung Guei, Lung-Pin Chen, I-Chen Wu, “Optimistic Temporal Difference Learning for 2048”, accepted by the IEEE Transactions on Games, 2021.<\/td>\n<\/tr>\n \n [3]<\/td>\n Jr-Chang Chen, Shih-Chieh Tang, I-Chen Wu, “Monte-Carlo Simulation for Mahjong”, accepted by Journal of Information Science and Engineering, 2021.<\/td>\n<\/tr>\n \n [4]<\/td>\n Hiroyuki Iida, Jonathan Schaeffer, I-Chen Wu, “The Computer Olympiad 2020”, ICGA Journal, Vol. 43, No. 2, June 2021.<\/td>\n<\/tr>\n \n [5]<\/td>\n Wenbo Gu, Lydia Leung, Ka Cheung Kwok, I-Chen Wu, Rodney J. Folz, Ambrose A. Chiang, “Belun Ring Platform: A Novel Home Sleep Apnea Testing System for Assessment of Obstructive Sleep Apnea”, Journal of Clinical Sleep Medicine, 16(9), (IF=3.456), September, 2020.<\/td>\n<\/tr>\n \n [6]<\/td>\n An-Jen Liu, Ti-Rong Wu, I-Chen Wu, Hung Guei, Tinghan Wei, “Strength Adjustment and Assessment for MCTS-Based Programs”, IEEE Computational Intelligence Magazine (IF=11.356), August 2020.<\/td>\n<\/tr>\n \n [7]<\/td>\n Jr-Chang Chen, Wen-Jie Tseng, I-Chen Wu, Tinghan Wei, “Comparison Training for Computer Chinese Chess,” the IEEE Transactions on Games, Vol. 12, No. 2, June 2020.<\/td>\n<\/tr>\n \n [8]<\/td>\n Wei-Yuan Hsu, Chu-Ling Ko, Jr-Chang Chen, Ting-Han Wei, Chu-Hsuan Hsueh, I-Chen Wu, “On Solving the 7,7,5-Game and the 8,8,5-Game”, Theoretical Computer Science, Vol. 815, pp. 79-94, May 2020.<\/td>\n<\/tr>\n \n [9]<\/td>\n Chen-Huan Pi, Kai-Chun Hu, Stone Cheng, I-Chen Wu, “Low-level autonomous control and tracking of quadrotor using reinforcement learning,” Control Engineering Practice, Vol. 95, February 2020.<\/td>\n<\/tr>\n \n [10]<\/td>\n Hung Guei, Tinghan Wei, I-Chen Wu, “2048-like games for teaching reinforcement learning”, ICGA Journal, Vol. 42, No. 1, January 2020.<\/td>\n<\/tr>\n \n [11]<\/td>\n C.-H. Hsueh and I-C. Wu, “EWIN wins EinStein W\u00fcrfelt Nicht! tournament”, ICGA Journal, Vol. 41, No. 1, March 2019.<\/td>\n<\/tr>\n \n [12]<\/td>\n Ti-Rong Wu, I-Chen Wu, Guan-Wun Chen, Ting-han Wei, Tung-Yi Lai, Hung-Chun Wu, Li-Cheng Lan, Multi-Labelled Value Networks for Computer Go, the IEEE Transactions on Games, Vol. 11, No. 4, pp 378-389, December 2018.<\/td>\n<\/tr>\n \n [13]<\/td>\n I-Chen Wu, Chang-Shing Lee, Yuandong Tian, and Martin Muller, Special Issue on Deep\/Reinforcement Learning and Games, the IEEE Transactions on Games, Vol. 11, No. 4, pp 333-335, December 2018.<\/td>\n<\/tr>\n \n [14]<\/td>\n Chung-Chin Shih, An-Jen. Liu and I-Chen Wu, “2017 CITIC Securities Cup \u2013 The 1st World AI Go Open”, ICGA Journal,Vol. 40, No. 4, December 2018.<\/td>\n<\/tr>\n \n [15]<\/td>\n J. Wang, T. Zhu, H. Li, C. H. Hsueh, and I-Chen Wu, Belief-state Monte-Carlo Tree Search for Phantom Go, the IEEE Transactions on Games, Vol. 10, No. 2, pp 139-154, June 2018.<\/td>\n<\/tr>\n \n [16]<\/td>\n Hsueh, C. H., I-Chen Wu, Hsu, T. S., & Chen Jr, C. An investigation of strength analysis metrics for game-playing programs: A case study in Chinese dark chess. ICGA Journal, Vol. 40, No. 2, June 2018.<\/td>\n<\/tr>\n \n [17]<\/td>\n Wen-Jie Tseng, Jr-Chang Chen, I-Chen Wu, Chimo wins Chinese chess tournament. ICGA Journal, Vol. 40, No. 2, June 2018.<\/td>\n<\/tr>\n \n [18]<\/td>\n Kun-Hao Yeh, I-Chen Wu, Chu-Hsuan Hsueh, Chia-Chuan Chang, Chao-Chin Liang, and Han Chiang, Multi-Stage Temporal Difference Learning for 2048-like Games, IEEE Transactions on Computational Intelligence and AI in Games, Vol. 10, No. 4, pp 369-380, December 2017.<\/td>\n<\/tr>\n \n [19]<\/td>\n W.-J. Tseng, Jr-Chang Chen, I-Chen Wu, “DarkKnight Wins Chinese Dark Chess Tournament”, ICGA Journal, Vol. 39(2), 163-165, June 2017.<\/td>\n<\/tr>\n \n [20]<\/td>\n J. Wang, C. Xiao, T. Zhu, C. H. Hsueh, W. J. Tseng, and I-Chen Wu, ONLY-ONE-VICTOR Pattern Learning in Computer Go, IEEE Transactions on Computational Intelligence and AI in Games, Vol. 9, No. 1, pp 88-102, 2017.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n \n\u7814\u8a0e\u6703\u8ad6\u6587<\/th>\n<\/tr>\n<\/tbody>\n \n [1]<\/td>\n Bo-Jiun Hsu, Hoang-Giang Cao, I Lee, Chih-Yu Kao, Jin-Bo Huang and I-Chen Wu, “Vision-Based Regularizing Action Policies for Smoothing Control in Autonomous Miniature Car Racing”, the Workshop of Artificial Intelligence for Autonomous Driving (AI4AD) at the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022), Messe Wien, Vienna, Austria, July 2022.<\/td>\n<\/tr>\n \n [2]<\/td>\n Bo-Jiun Hsu, Hoang-Giang Cao, I Lee, Chih-Yu Kao, Jin-Bo Huang and I-Chen Wu, “Image-Based Conditioning for Action Policy Smoothness in Autonomous Miniature Car Racing with Reinforcement Learning”, the 2nd Workshop on Opportunities and Challenges with Autonomous Racing at IEEE International Conference on Robotics and Automation (ICRA 2022), Philadelphia, May 2022.<\/td>\n<\/tr>\n \n [3]<\/td>\n Hoang-Giang Cao, Weihao Zeng, I-Chen Wu, “Reinforcement Learning for Picking Cluttered General Objects with Dense Object Descriptors”, IEEE International Conference on Robotics and Automation (ICRA 2022), Philadelphia, May 2022. (Acceptance rate: 1,428\/3,313 \u2248 43.1%)<\/td>\n<\/tr>\n \n [4]<\/td>\n 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 2022), April 2022. (Acceptance rate: 1,095\/3,391 \u2248 32.3%)<\/td>\n<\/tr>\n \n [5]<\/td>\n Chung-Chin Shih, Ti-Rong Wu, Tinghan 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), February 2022. (Acceptance rate: 1349\/9020 ~= 15%)<\/td>\n<\/tr>\n \n [6]<\/td>\n Hoang-Giang Cao, Weihao Zeng, I-Chen Wu, “Using Dense Object Descriptors for Picking Cluttered General Objects with Reinforcement Learning”, the NeurIPS 2021 4th Robot Learning Workshop: Self-Supervised and Lifelong Learning, December, 2021.<\/td>\n<\/tr>\n \n [7]<\/td>\n Chiu-Chou Lin, Wei-Chen Chiu, I-Chen Wu, “An Unsupervised Video Game Playstyle Metric via State Discretization”, the 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021), July 2021. (Acceptance rate: 206\/777 ~= 26.5%)<\/td>\n<\/tr>\n \n [8]<\/td>\n Shao-Xiong Zheng, Wei-Yuan Hsu, Kuo-Chan Huang, I-Chen Wu, “Connect6 Opening Leveraging AlphaZero and Job-Level Computing”, The 35th Annual Conference of The Japanese Society for Artificial Intelligence (JSAI 2021), Japan, June 2021.<\/td>\n<\/tr>\n \n [9]<\/td>\n Li-Cheng Lan, Meng-Yu Tsai, 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), arXiv:2012.07910, February 2021. (Acceptance rate: 1,692\/7,911 ~= 21.4%)<\/td>\n<\/tr>\n \n [10]<\/td>\n Kai-Chun Hu, Ping-Chun Hsieh, Ting Han Wei, I-Chen Wu, “Rethinking Deep Policy Gradients via State-Wise Policy Improvement”, ICBINB Workshop, in the Thirty-fourth Annual Conference on Neural Information Processing Systems (NeurIPS 2020), Decemeber 2020.<\/td>\n<\/tr>\n \n [11]<\/td>\n Yeong-Jia Roger Chu, Tinghan Wei, Jin-Bo Huang, Yuan-Hao Chen, I-Chen Wu, “Sim-To-Real Transfer for Autonomous Miniature Car Racing”, Workshop on Perception, Learning, and Control for Autonomous Agile Vehicles, in the International Conference on Intelligent Robots and Systems (IROS), Las Vegas, October 2020.<\/td>\n<\/tr>\n \n [12]<\/td>\n Chu-Hsuan Hsueh, Kokolo Ikeda, Sang-Gyu Nam, I-Chen Wu, “Analyses of Tabular AlphaZero on NoGo,” the 2020 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2020), Taipei, Taiwan, December 2020. (Best Poster Award)<\/td>\n<\/tr>\n \n [13]<\/td>\n Kuo-Hao Ho, Pei-Shu Huang, I-Chen Wu, Feng-Jian Wang, “Prediction of Time Series Data Based on Transformer with Soft Dynamic Time Wrapping”, IEEE International Conference on Consumer Electronics – Taiwan (ICCE-TW), September 2020.<\/td>\n<\/tr>\n \n [14]<\/td>\n Ti-Rong Wu, Tinghan Wei, I-Chen Wu, “Accelerating and Improving AlphaZero Using Population Based Training”, the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), February 2020. (Acceptance rate: 1591\/7737 ~= 20.6%) (Oral Presentation 453\/7737 ~= 5.85%)<\/td>\n<\/tr>\n \n [15]<\/td>\n Tong-Yi Lai, Chu-Hsuan Hsueh, You-Hsuan Lin, Yeong-Jia Roger Chu, Bo-Yang Hsueh and I-Chen Wu, “Combining Deep Deterministic Policy Gradientwith Cross-Entropy Method,” the 2019 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2019), Kaohsiung, Taiwan, November 2019.<\/td>\n<\/tr>\n \n [16]<\/td>\n Wen-Jie Tseng, Jr-Chang Chen and I-Chen Wu, “Merging Metrics of Special Rules in Chinese Chess Endgame Databases,” the 2019 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2019), Kaohsiung, Taiwan, November 2019.<\/td>\n<\/tr>\n \n [17]<\/td>\n Lung-Pin Chen, I-Chen Wu and Yen-Ling Chang, “Reinforcement Learning based Fragment-Aware Scheduling for High Utilization HPC Platforms,” the 2019 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2019), Kaohsiung, Taiwan, November 2019.<\/td>\n<\/tr>\n \n [18]<\/td>\n Hsiao-Chung Hsieh, Ti-Rong Wu, Ting-Han Wei, and I-Chen Wu, “Net2Net Extension for the AlphaGo Zero Algorithm”. In the 16th conference on Advances in Computer Games (ACG2019), Macau, China, 2019.<\/td>\n<\/tr>\n \n [19]<\/td>\n Li-Cheng Lan, Wei Li, Tinghan Wei, I-Chen Wu, “Multiple Policy Value Monte Carlo Tree Search”, the 28th International Joint Conference on Artificial Intelligence (IJCAI-19), Macau, China, August 2019. (Acceptance rate: 850\/4752 = 17.9%)<\/td>\n<\/tr>\n \n [20]<\/td>\n Hung Guei, Tinghan Wei, I-Chen Wu, “Teaching Reinforcement Learning and Computer Games with 2048-Like Games”, The 33th Annual Conference of The Japanese Society for Artificial Intelligence (JSAI 2019), Niigata, Japan, June 2019.<\/td>\n<\/tr>\n \n [21]<\/td>\n 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), January 2019. (Acceptance rate: 1150\/7095 = 16.2%)<\/td>\n<\/tr>\n \n [22]<\/td>\n Bo-Yang Hsueh, Wei Li, I-Chen Wu, “Stochastic Gradient Descent with Hyperbolic-Tangent Decay”, IEEE Winter Conference on Applications of Computer Vision (WACV 2019), January 2019.<\/td>\n<\/tr>\n \n [23]<\/td>\n Ming-Xu Huang, I-Chen Wu, Bo-Yang Hsueh, Tinghan Wei, Pei-Shu Huang, “Visual-Based Parameterized Proximal Policy Optimization”, Infer to Control: Workshop on Probabilistic Reinforcement Learning and Structured Control, in the Thirty-second Annual Conference on Neural Information Processing Systems (NIPS 2018), Decemeber 2018.<\/td>\n<\/tr>\n \n [24]<\/td>\n Chu-Hsuan Hsueh, I-Chen Wu, Jr-Chang Chen, Tsan-sheng Hsu, “AlphaZero for a Non-deterministic Game,” the 2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2018), Taichung, Taiwan, December 2018. (Best Paper Award)<\/td>\n<\/tr>\n \n [25]<\/td>\n Chung-Chin Shih, Ting han Wei, Zheng-Yuan Lee, I-Chen Wu, “Playing Games with the Job-Level Computation System,” the 23rd Game Programming Workshop (GPW-2018), Kanagawa, Japan, November 16-18, 2018.<\/td>\n<\/tr>\n \n [26]<\/td>\n Wen-Jie Tseng, Jr-Chang Chen, I-Chen Wu, “Comparison Training of N-Tuple Networks for Chess,” the 23rd Game Programming Workshop (GPW-2018), Kanagawa, Japan, November 16-18, 2018.<\/td>\n<\/tr>\n \n [27]<\/td>\n Guei, H., Wei, T. H., and I-Chen Wu. Using 2048-like Games as a Pedagogical Tool for Reinforcement Learning. International Conference on Computers and Games (CG2018), New Taipei City, Taiwan, July 2018.<\/td>\n<\/tr>\n \n [28]<\/td>\n Hsu W. Y., Ko C. L., Hsueh C. H., and I-Chen Wu. Solving 7,7,5-Game and 8,8,5-Game. International Conference on Computers and Games (CG2018), New Taipei City, Taiwan, July 2018.<\/td>\n<\/tr>\n \n [29]<\/td>\n Yeong-Jia Roger Chu, Yuan-Hao Chen, Chu-Hsuan Hsueh, I-Chen Wu, “An Agent That Plays EinStein Wurfelt Nicht!”, the 2017 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2017), Taipei, Taiwan, December 2017. (Merit Paper Award)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n
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