Meta-Optimization of Bias-Variance Trade-Off in Stochastic Model Learning
Model-based reinforcement learning is expected to be a method that can safely acquire the optimal policy under real-world conditions by using a stochastic dynamics model for planning. Since the stochastic dynamics model of the real world is generally unknown, a method for learning from state transit...
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Auteurs principaux: | Takumi Aotani, Taisuke Kobayashi, Kenji Sugimoto |
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Format: | article |
Langue: | EN |
Publié: |
IEEE
2021
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Sujets: | |
Accès en ligne: | https://doaj.org/article/af14030d799748c8865f08da2aa6ba56 |
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