A State Space Compression Method Based on Multivariate Analysis for Reinforcement Learning in High-Dimensional Continuous State Spaces

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A State Space Compression Method Based on Multivariate Analysis for Reinforcement Learning in High-Dimensional Continuous State Spaces

SUMMARY A state space compression method based on multivariate analysis was developed and applied to reinforcement learning for high-dimensional continuous state spaces. First, useful components in the state variables of an environment are extracted and meaningless ones are removed by using multiple regression analysis. Next, the state space of the environment is compressed by using principal c...

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ژورنال

عنوان ژورنال: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

سال: 2006

ISSN: 0916-8508,1745-1337

DOI: 10.1093/ietfec/e89-a.8.2181