New quantum algorithms compute near-optimal policies for finite-horizon MDPs with Õ(H^{2.5}S√A/ε) queries and for infinite-horizon discounted MDPs with Õ(Γ^{2.5}S√A/ε) queries, improving all previously known quantum upper bounds.
An introduction to quantum machine learning: from quantum logic to quantum deep learning.Quantum Machine Intelligence, 3(2):28, Nov 2021
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Improved Quantum Algorithms for Reinforcement Learning Under a Generative Model
New quantum algorithms compute near-optimal policies for finite-horizon MDPs with Õ(H^{2.5}S√A/ε) queries and for infinite-horizon discounted MDPs with Õ(Γ^{2.5}S√A/ε) queries, improving all previously known quantum upper bounds.