Continuous Valued Q-learning for Vision-Guided Behavior A quisition
نویسندگان
چکیده
منابع مشابه
Continuous Valued Q-learning for Vision-Guided Behavior Acquisition
Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to real robot tasks because of poor performance of learned behavior and further a new problem of state space construction. This paper proposes a continuous valued Q-learning for real robot applications, which calculates co...
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Q-learning, a most widely used reinforcement learning method, normally needs well-de ned quantized state and action spaces to converge. This makes it di cult to be applied to real robot tasks because of poor performance of learned behavior and further a new problem of state space construction. We have proposed Continuous Valued Q-learning for real robot applications, which calculates contributi...
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Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to obtain an optimal policy for accomplishing a given task. This makes it difficult to be applied to real robot tasks because of poor performance of learned behavior due to the failure of quantization of continuous state and action spaces. To deal with this problem, we pro...
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