Predictive Timing Models
نویسندگان
چکیده
We consider the problems of learning and planning in Markov decision processes with temporally extended actions represented in the options framework. We propose to use predictions about the duration of extended actions to represent the state and show how this leads to a compact predictive state representation model independent of the set of primitive actions. Then we develop a consistent and efficient spectral learning algorithm for such models.
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تاریخ انتشار 2014