Comments (5)
@guotong1988 I do not quite understand your question. But every transition is recorded as a 4 element tuple in the deque. You should note that the reward is a instant reflection of the environment. I really think you should learn the very basic concept of Markov Reward Process and Markov Decision Process first before reinforcement learning.
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看这里,reward为1和-1都只能被sample出来然后feed进去,这样只有被sample出来才能起作用
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@guotong1988 i see, you are right, thus the author implied that prioritized experience replay can potentially optimize your problem by improving the probability of a more significant transition being chosen in another issue.
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Oh,it's here,Thank you !
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@guotong1988 You are welcome,:)
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