Quantum POMDPs
Abstract
We present quantum observable Markov decision processes (QOMDPs), the quantum analogues of partially observable Markov decision processes (POMDPs). In a QOMDP, an agent's 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.
Keywords
Cite
@article{arxiv.1406.2858,
title = {Quantum POMDPs},
author = {Jennifer Barry and Daniel T. Barry and Scott Aaronson},
journal= {arXiv preprint arXiv:1406.2858},
year = {2015}
}
Comments
13 pages, 3 figures, revised version (fixes several errors, discusses related work)