qlan3 / QuantumExplorer
A quantum reinforcement learning framework based on PyTorch and PennyLane.
☆24Updated 9 months ago
Related projects ⓘ
Alternatives and complementary repositories for QuantumExplorer
- PennyLane/PyTorch implementation of Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning (Skolik et al., 2021)☆36Updated last year
- Cirq/PyTorch implementation of Quantum Architecture Search via Deep Reinforcement Learning by (Kuo et al., 2021)☆38Updated 3 years ago
- Quantum Multi-agent Reinforcement Learning (QMARL)☆26Updated 2 years ago
- Variational Quantum Circuits for Deep Reinforcement Learning since 2019. Xanadu Quantum Software Competition 1st Prize 2019.☆57Updated 3 years ago
- Reinforcement Learning Enhanced Quantum-inspired Algorithm for Combinatorial Optimization☆13Updated 4 years ago
- Study of entanglement and Shannon entropies in Quantum Reinforcement Learning (and its classical counterpart) in a discrete environment.☆16Updated 2 years ago
- ☆15Updated last month
- Implementation of QRL☆28Updated 5 years ago
- Code for Shapley values for explaining reinforcement learning. XRL feature-influence method.☆15Updated 11 months ago
- A library for mean-field games.☆45Updated this week
- This repo is the implementation of paper ''SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning''.☆41Updated 11 months ago
- Code for "Optimizing Quantum Variational Circuits with Deep Reinforcement Learning"☆15Updated 6 months ago
- GitHub repo for Qiskit Hackathon "Quantum Reinforcement Learning" project☆30Updated 6 months ago
- Source code for the Paper: CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints}☆72Updated 2 years ago
- Efficient Exploration through Bayesian Deep-Q Networks.☆17Updated 2 years ago
- reinforcement learning with pytorch geometric library☆45Updated 3 years ago
- Official pytorch implementation for our ICLR 2023 paper "Latent State Marginalization as a Low-cost Approach for Improving Exploration".☆24Updated last year
- PyTorch implementation of "Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs", NeurIPS 2020☆38Updated 4 years ago
- Pytorch implementation of Soft Actor-Critic☆18Updated 4 years ago
- An implementation of the 2016 meta-learning paper "Learning to Optimize" from the BAIR lab at Berkeley.☆19Updated 3 years ago
- Code to run the ASEBO algorithm from the paper: From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization... …☆16Updated 4 years ago
- Experiment for Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning☆24Updated last year
- Our version of #Exploration: A Study of Count-Based Explorationfor Deep Reinforcement Learning for a class project☆14Updated 3 years ago
- Population-Based Reinforcement Learning for Combinatorial Optimization☆65Updated 9 months ago
- Reinforcement Learning Environments for Sustainable Energy Systems☆39Updated 5 months ago
- Official implementation of NeurIPS'22 paper "Monte Carlo Tree Search based Variable Selection for High-Dimensional Bayesian Optimization"☆30Updated last year
- Reinforcement Learning with Perturbed Reward, AAAI 2020☆28Updated 3 months ago
- Experiments on a discrete mean field game model of population dynamics with reinforcement learning☆31Updated last year
- Plug-and-play hydra sweepers for the EA-based multifidelity method DEHB and several population-based training variations, all proven to e…☆70Updated 11 months ago
- Code for the paper: "Causal Influence Detection for Improving Efficiency in Reinforcement Learning", by Seitzer, M., Schölkopf, B., Marti…☆36Updated 2 years ago