PennyLane/PyTorch implementation of Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning (Skolik et al., 2021)
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Updated
Mar 15, 2023 - Python
PennyLane/PyTorch implementation of Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning (Skolik et al., 2021)
Study of entanglement and Shannon entropies in Quantum Reinforcement Learning (and its classical counterpart) in a discrete environment.
A quantum reinforcement learning framework based on PyTorch and PennyLane.
Comparative study: Quantum vs. classical models for Cart Pole. Examining entanglement layers and data re-uploading, highlighting quantum model superiority.
GitHub repo for Qiskit Hackathon "Quantum Reinforcement Learning" project
Study of entanglement and Shannon entropies in Quantum Reinforcement Learning (and its classical counterpart) in a discrete environment.
Reinforcement Learning with Variational Quantum Circuits
PennyLane/PyTorch implementation of Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning (Skolik et al., 2021)
Implementation of proof of concept quantum enhanced reinforced learning algorithm, able to find the sequence of quantum gates needed to approximate a given function.
Variational Quantum Circuits for Deep Reinforcement Learning since 2019. Xanadu Quantum Software Competition 1st Prize 2019.
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