Resultados de búsqueda - Wu, Ti-Rong

Strength Estimation and Human-Like Strength Adjustment in Games por Chen, Chun Jung, Shih, Chung-Chin, Wu, Ti-Rong

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Dynamic Sight Range Selection in Multi-Agent Reinforcement Learning por Liao, Wei-Chen, Wu, Ti-Rong, Wu, I-Chen

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Demystifying MuZero Planning: Interpreting the Learned Model por Guei, Hung, Ju, Yan-Ru, Chen, Wei-Yu, Wu, Ti-Rong

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OptionZero: Planning with Learned Options por Huang, Po-Wei, Peng, Pei-Chiun, Guei, Hung, Wu, Ti-Rong

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MAPLE: Multi-State Aggregated Policy Evaluation for AlphaZero in Imperfect-Information Games por Li, Qian-Rong, Guei, Hung, Wu, I-Chen, Wu, Ti-Rong

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A Novel Approach to Solving Goal-Achieving Problems for Board Games por Shih, Chung-Chin, Wu, Ti-Rong, Wei, Ting Han, Wu, I-Chen

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Bridging Local and Global Knowledge via Transformer in Board Games por Ju, Yan-Ru, Wu, Tai-Lin, Shih, Chung-Chin, Wu, Ti-Rong

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Regret-Guided Search Control for Efficient Learning in AlphaZero por Tsai, Yun-Jui, Chen, Wei-Yu, Ju, Yan-Ru, Chang, Yu-Hung, Wu, Ti-Rong

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A Study of Solving Life-and-Death Problems in Go Using Relevance-Zone Based Solvers por Shih, Chung-Chin, Wu, Ti-Rong, Wei, Ting Han, Hsu, Yu-Shan, Guei, Hung, Wu, I-Chen

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Evaluating Game Difficulty in Tetris Block Puzzle por Wang, Chun-Jui, Guo, Jian-Ting, Guei, Hung, Shih, Chung-Chin, Wu, Ti-Rong, Wu, I-Chen

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MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games por Wu, Ti-Rong, Guei, Hung, Peng, Pei-Chiun, Huang, Po-Wei, Wei, Ting Han, Shih, Chung-Chin, Tsai, Yun-Jui

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Solving 7x7 Killall-Go with Seki Database por Tsai, Yun-Jui, Wei, Ting Han, Lin, Chi-Huang, Shih, Chung-Chin, Guei, Hung, Wu, I-Chen, Wu, Ti-Rong

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Learning Human-Like RL Agents Through Trajectory Optimization With Action Quantization por Guo, Jian-Ting, Chen, Yu-Cheng, Hsieh, Ping-Chun, Ho, Kuo-Hao, Huang, Po-Wei, Wu, Ti-Rong, Wu, I-Chen

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Relevance-Zone Reduction in Game Solving por Lin, Chi-Huang, Wei, Ting Han, Wang, Chun-Jui, Guei, Hung, Shih, Chung-Chin, Tsai, Yun-Jui, Wu, I-Chen, Wu, Ti-Rong

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MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs por Wang, Kevin, Thöni, Anna, Kempinski, Benjamin, Cheng, Bobby, Yao, Jianzhu, Finch, Benjamin, Guertler, Leon, Nadkarni, Viraj, Jiang, Yihan, Korshuk, Aliaksei, Buyantuev, Alexander, Makarov, Ilya, Wu, Siyuan, Cheng, Yu-Chi, Ju, Yan-Ru, Wu, Ti-Rong, Chu, I-Hsuan, Yang, Yu-Yu, Wu, I-Chen, Huang, Yitian, Cao, Qinlu, Sun, Yiheng, Dai, Yuhong, Yao, Hongkun, Fu, Jingxuan, Zhang, Jiwei, Liao, Hao, Ebeling, Mossimo, Arun, Govind, Bathini, Sadhvik, Arya, Mihir S, Anish, Avinash, Ranjan, Aditya, Phatnani, Kirtana Sunil, KS, Paval, Mehta, Vrushali, S, Aravind, Arora, Nikhil, Upadhyay, Tanya, Bandagale, Amol, Lu, Yuan, Hsiao, ChunEn, Lin, YuTing, Chung, Arvin, Thomas, Jerry John, Laurière, Mathieu, Choshen, Leshem, Bachrach, Yoram, Viswanath, Pramod, Polukarov, Maria, Tan, Cheston, Kachman, Tal, Wang, Atlas

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