There are no reviews yet. Be the first to send feedback to the community and the maintainers!
Soft-Actor-Critic-and-Extensions
PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.DQN-Atari-Agents
DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQNCQL
PyTorch implementation of the Offline Reinforcement Learning algorithm CQL. Includes the versions DQN-CQL and SAC-CQL for discrete and continuous action spaces.Upside-Down-Reinforcement-Learning
Upside-Down Reinforcement Learning (โ ๊ค) implementation in PyTorch. Based on the paper published by Jรผrgen Schmidhuber.Deep-Reinforcement-Learning-Algorithm-Collection
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.Munchausen-RL
PyTorch implementation of the Munchausen Reinforcement Learning Algorithms M-DQN and M-IQNSAC_discrete
PyTorch implementation of the discrete Soft-Actor-Critic algorithm.Implicit-Q-Learning
PyTorch implementation of the implicit Q-learning algorithm (IQL)FQF-and-Extensions
PyTorch implementation of the state-of-the-art distributional reinforcement learning algorithm Fully Parameterized Quantile Function (FQF) and Extensions: N-step Bootstrapping, PER, Noisy Layer, Dueling Networks, and parallelization.QR-DQN
PyTorch implementation of QR-DQN: Distributional Reinforcement Learning with Quantile RegressionNormalized-Advantage-Function-NAF-
PyTorch implementation of the Q-Learning Algorithm Normalized Advantage Function for continuous control problems + PER and N-step MethodRandomized-Ensembled-Double-Q-learning-REDQ-
Pytorch implementation of Randomized Ensembled Double Q-learning (REDQ)D4PG
PyTorch implementation of D4PG with the SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.GANs
ClusterGAN PyTorch implementationMedium_Code_Examples
Implementation of fundamental concepts and algorithms for reinforcement learningOFENet
Genetic-Algorithms-Neural-Network-Optimization
Genetic Algorithm for Neural Network Architecture and Hyperparameter Optimization and Neural Network Weight Optimization with Genetic AlgorithmGARNE-Genetic-Algorithm-with-Recurrent-Network-and-Novelty-Exploration
GARNE: Genetic-Algorithm-with-Recurrent-Network-and-Novelty-ExplorationMBPO
Hindsight-Experience-Replay
D4PG-ray
Distributed PyTorch implementation of D4PG with ray. Using a SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.pytorch-vmpo
PyTorch implementation of V-MPOPETS-MPC
RA-PPO
PyTorch implementation of Risk-Averse Policy LearningUdacity-DRL-Nanodegree-P3-Multiagent-RL-
Multi-Agent-RL Competition on Unitys Tennis EnvironmentCEN-Network
TD3-and-Extensions
PyTorch implementation of Twin Delayed Deep Deterministic Policy Gradient (TD3) - including additional Extension to improve the algorithm's performance.DRQN
Love Open Source and this site? Check out how you can help us