Difference between revisions of "Yasuhiro Osaki"
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− | Yasuhiro Osaki's research was about [[Reinforcement Learning|reinforcement learning]] and the application of [[Temporal Difference Learning|TD(λ)]] based on [https://en.wikipedia.org/wiki/Monte_Carlo_method Monte-Carlo simulations] in computer games. The program committee of the [[Conferences#GPW|12th Game Programming Workshop 2007]] gave the best presentation award to Yasuhiro Osaki on '''TD(λ)-MC''', a reinforcement learning approach with Monte-carlo simulations <ref>[[Yasuhiro Osaki]], [[Kazutomo Shibahara]], [[Yasuhiro Tajima]], [[Yoshiyuki Kotani]] ('''2007'''). ''Reinforcement Learning of Evaluation Functions Using Temporal Difference-Monte Carlo learning method''. [[Conferences#GPW|12th Game Programming Workshop]] | + | Yasuhiro Osaki's research was about [[Reinforcement Learning|reinforcement learning]] and the application of [[Temporal Difference Learning|TD(λ)]] based on [https://en.wikipedia.org/wiki/Monte_Carlo_method Monte-Carlo simulations] in computer games. The program committee of the [[Conferences#GPW|12th Game Programming Workshop 2007]] gave the best presentation award to Yasuhiro Osaki on '''TD(λ)-MC''', a reinforcement learning approach with Monte-carlo simulations <ref>[[Yasuhiro Osaki]], [[Kazutomo Shibahara]], [[Yasuhiro Tajima]], [[Yoshiyuki Kotani]] ('''2007'''). ''Reinforcement Learning of Evaluation Functions Using Temporal Difference-Monte Carlo learning method''. [[Conferences#GPW|12th Game Programming Workshop]]</ref> <ref>[https://en.wikipedia.org/wiki/Temporal_difference_learning#Mathematical_formulation TD-Lamda from Wikipedia]</ref>. |
=Selected Publications= | =Selected Publications= |
Revision as of 13:11, 7 March 2019
Home * People * Yasuhiro Osaki
Yasuhiro Osaki,
a Japanese software engineer and computer scientist at Sony. Until 2010, Yasuhiro Osaki was affiliated with the laboratory of professor Yoshiyuki Kotani at the Tokyo University of Agriculture and Technology.
TD(λ)-MC
Yasuhiro Osaki's research was about reinforcement learning and the application of TD(λ) based on Monte-Carlo simulations in computer games. The program committee of the 12th Game Programming Workshop 2007 gave the best presentation award to Yasuhiro Osaki on TD(λ)-MC, a reinforcement learning approach with Monte-carlo simulations [2] [3].
Selected Publications
- Yasuhiro Osaki, Kazutomo Shibahara, Yasuhiro Tajima, Yoshiyuki Kotani (2007). Reinforcement Learning of Evaluation Functions Using Temporal Difference-Monte Carlo learning method. 12th Game Programming Workshop
- Yasuhiro Osaki, Kazutomo Shibahara, Yasuhiro Tajima, Yoshiyuki Kotani (2008). An Othello Evaluation Function Based on Temporal Difference Learning using Probability of Winning. CIG'08, pdf
- Yasuhiro Osaki, Yoshiyuki Kotani (2009). A Learning Method of Evaluation Function Based on Selective Simulations. 14th Game Programming Workshop
External Links
References
- ↑ YasuhiroOsaki (Yasuhiro Osaki) · GitHub
- ↑ Yasuhiro Osaki, Kazutomo Shibahara, Yasuhiro Tajima, Yoshiyuki Kotani (2007). Reinforcement Learning of Evaluation Functions Using Temporal Difference-Monte Carlo learning method. 12th Game Programming Workshop
- ↑ TD-Lamda from Wikipedia
- ↑ dblp: Yasuhiro Osaki