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|a Barry, Jennifer
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Aaronson, Scott
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|a Barry, Daniel T.
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|a Aaronson, Scott
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|a Quantum partially observable Markov decision processes
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|b American Physical Society,
|c 2014-09-12T17:39:21Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/89468
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|a We present quantum observable Markov decision processes (QOMDPs), the quantum analogs of partially observable Markov decision processes (POMDPs). In a QOMDP, an agent is acting in a world where the state is represented as a quantum state and the agent can choose a superoperator to apply. This is similar to the POMDP belief state, which is a probability distribution over world states and evolves via a stochastic matrix. We show that the existence of a policy of at least a certain value has the same complexity for QOMDPs and POMDPs in the polynomial and infinite horizon cases. However, we also prove that the existence of a policy that can reach a goal state is decidable for goal POMDPs and undecidable for goal QOMDPs.
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|a National Science Foundation (U.S.) (Grant 0844626)
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|a National Science Foundation (U.S.) (Grant 1122374)
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|a National Science Foundation (U.S.) (Waterman Award)
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|a Article
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|t Physical Review A
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