Automatic shaping and decomposition of reward functions
This paper investigates the problem of automatically learning how torestructure the reward function of a Markov decision process so as tospeed up reinforcement learning. We begin by describing a method thatlearns a shaped reward function given a set of state and temporalabstractions. Next, we cons...
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2007
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| Online Access: | http://hdl.handle.net/1721.1/35890 |