PennyLane/PyTorch implementation of Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning (Skolik et al., 2021)

A quantum reinforcement learning framework based on PyTorch and PennyLane.

Study of entanglement and Shannon entropies in Quantum Reinforcement Learning (and its classical counterpart) in a discrete environment.

Clean and easy to understand implementations of many Quantum Reinforcement Learning agents as well as their classical analouges. Greately inspired by the orgininal CleanRL

Comparative study: Quantum vs. classical models for Cart Pole. Examining entanglement layers and data re-uploading, highlighting quantum model superiority.

Clean and easy to understand implementations of many Quantum Reinforcement Learning agents as well as their classical analouges. Greately inspired by the orgininal [CleanRL](https://github.com/vwxyzjn/cleanrl)

Implementation of proof of concept quantum enhanced reinforced learning algorithm, able to find the sequence of quantum gates needed to approximate a given function.

GitHub repo for Qiskit Hackathon "Quantum Reinforcement Learning" project

QRLIT: Quantum Reinforcement Learning for Database Index Tuning

This repository contains the source code and results for the experiments presented in Evaluating Parameter-Based Training Performance of Neural Networks and Variational Quantum Circuits.

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)

Variational Quantum Circuits for Deep Reinforcement Learning since 2019. Xanadu Quantum Software Competition 1st Prize 2019.

Python library for hybrid quantum-classical reinforcement learning agents using PennyLane and Gymnasium.