ikostrikov / pytorch-a2c-ppo-acktr-gailLinks
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
☆3,790Updated 3 years ago
Alternatives and similar repositories for pytorch-a2c-ppo-acktr-gail
Users that are interested in pytorch-a2c-ppo-acktr-gail are comparing it to the libraries listed below
Sorting:
- Collection of reinforcement learning algorithms☆2,711Updated last year
- PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".☆1,280Updated 5 years ago
- Modularized Implementation of Deep RL Algorithms in PyTorch☆3,314Updated last year
- Rainbow: Combining Improvements in Deep Reinforcement Learning☆1,630Updated 3 years ago
- Reinforcement Learning in PyTorch☆2,262Updated 4 years ago
- Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official imp…☆1,310Updated last year
- PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Lear…☆1,225Updated 4 years ago
- Author's PyTorch implementation of TD3 for OpenAI gym tasks☆1,893Updated last year
- Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL☆3,112Updated 3 years ago
- Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow☆1,962Updated last month
- A fork of OpenAI Baselines, implementations of reinforcement learning algorithms☆4,286Updated 2 years ago
- PyTorch implementations of deep reinforcement learning algorithms and environments☆5,830Updated 11 months ago
- Python Multi-Agent Reinforcement Learning framework☆2,038Updated 2 years ago
- rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.☆2,973Updated 2 years ago
- Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"☆2,592Updated last year
- Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)☆3,022Updated 2 years ago
- A toolkit for reproducible reinforcement learning research.☆1,988Updated 2 years ago
- Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch☆1,080Updated 4 years ago
- PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT…☆1,256Updated 3 months ago
- PyTorch implementation of soft actor critic☆887Updated 3 years ago
- Soft Actor-Critic☆1,109Updated last year
- Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillio…☆3,393Updated last year
- A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.☆1,181Updated 2 years ago
- Simple and easily configurable grid world environments for reinforcement learning☆2,267Updated last week
- Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch☆2,082Updated 11 months ago
- Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"☆1,820Updated last year
- A Platform for Many-Agent Reinforcement Learning☆1,741Updated 2 years ago
- Policy Gradient is all you need! A step-by-step tutorial for well-known PG methods.☆938Updated last month
- For deep RL and the future of AI.☆1,470Updated last year
- SMAC: The StarCraft Multi-Agent Challenge☆1,221Updated last year