Parallel reinforcement learning for weighted multi-criteria model with adaptive margin |
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Authors: | Kazuyuki Hiraoka Manabu Yoshida Taketoshi Mishima |
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Affiliation: | (1) Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, Japan |
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Abstract: | Reinforcement learning (RL) for a linear family of tasks is described in this paper. The key of our discussion is nonlinearity of the optimal solution even if the task family is linear; we cannot obtain the optimal policy using a naive approach. Although an algorithm exists for calculating the equivalent result to Q-learning for each task simultaneously, it presents the problem of explosion of set sizes. We therefore introduce adaptive margins to overcome this difficulty. |
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Keywords: | Reinforcement learning Multi-criteria Convex hull Minkowski sum |
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