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- W2574367019 abstract "An input generalization problem is one of the most important in applying reinforcement learning to real robot tasks. To cope with this problem, we propose a self-partitioning state space algorithm, which can make nonuniform quantization of state space. To show that our algorithm has generalization capability, we apply our method to two tasks in which a soccer robot shoots a ball into a goal and prevent a ball from entering a goal. To show the validity of this method, the experimental results for computer simulation and a real robot are shown." @default.
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- W2574367019 date "2001-12-20" @default.
- W2574367019 modified "2023-09-26" @default.
- W2574367019 title "Self-Partitioning State Space for Behavior Acquisition of Vision-Based Mobile Robots" @default.
- W2574367019 doi "https://doi.org/10.20965/jrm.2001.p0625" @default.
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