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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]], [http://www.tuat.ac.jp/~kotani/index.php?plugin=attach&pcmd=open&file=osaki0711TDMC-GPW%29.pdf&refer=lab%2Fpapers%2Fdepot pdf] (Japanese)</ref> <ref>[https://en.wikipedia.org/wiki/Temporal_difference_learning#Mathematical_formulation TD-Lamda from Wikipedia]</ref>.