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Found 2 papers, 1 papers with code
Learning Markov State Abstractions for Deep Reinforcement Learning
A fundamental assumption of reinforcement learning in Markov decision processes (MDPs) is that the relevant decision process is, in fact, Markov.
Deep Radial-Basis Value Functions for Continuous Control
We show that the maximum action-value with respect to a deep RBVF can be approximated easily and accurately.
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