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Research achievement detail

Title Active Learning Strategy for Role - playing Game Modeled by Markov Decision Processes (in Japanese)
Authors Yasunari MAEDA 、Fumitaro GOTO 、Hiroshi MASUI 、Fumito MASUI 、Masakiyo SUZUKI 、Toshiyasu MATSUSHIMA
Released Year 2013
Format Journal
Category Knowledge information processing
Jounal Name Journal of Biomedical Fuzzy Systems Association
Jounal Page vol.15, no.1, pp.69-81
Published Year 2013
Published Month 6
Abstract
(English)
In previous research a role-playing game(RPG) is represented with Markov decision processes(MDP). But active learning method for RPG has not been studied yet. In this research we propose an active learning method which maximizes an expected total reward with respect to a Bayes criterion under the condition that the true parameter of MDP is unknown. We recognize the effectiveness of our proposed method by some simulations.
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(English)
3
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