# A hybrid classical-quantum approach to speed-up Q-learning

@inproceedings{Sannia2022AHC, title={A hybrid classical-quantum approach to speed-up Q-learning}, author={Antonello Sannia and Alessandro Giordano and N. Lo Gullo and Carlo Mastroianni and Francesco Plastina}, year={2022} }

We introduce a classical-quantum hybrid approach to computation, allowing for a quadratic performance improvement in the decision process of a learning agent. In particular, a quantum routine is described, which encodes on a quantum register the probability distributions that drive action choices in a reinforcement learning set-up. This routine can be employed by itself in several other contexts where decisions are driven by probabilities. After introducing the algorithm and formally evaluating…

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