google-deepmind / dqn_zooLinks
DQN Zoo is a collection of reference implementations of reinforcement learning agents developed at DeepMind based on the Deep Q-Network (DQN) agent.
☆475Updated last year
Alternatives and similar repositories for dqn_zoo
Users that are interested in dqn_zoo are comparing it to the libraries listed below
Sorting:
- A Python interface for reinforcement learning environments☆377Updated 2 years ago
- Offline Reinforcement Learning (aka Batch Reinforcement Learning) on Atari 2600 games☆555Updated 2 years ago
- JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.☆709Updated 2 years ago
- A PyTorch Platform for Distributed RL☆750Updated 3 years ago
- Code for Go-Explore: a New Approach for Hard-Exploration Problems☆575Updated 2 years ago
- Pytorch Implementation of MuZero☆353Updated 2 years ago
- Tools for accelerating safe exploration research.☆552Updated 2 years ago
- RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code☆702Updated last year
- Code for the paper "Phasic Policy Gradient"☆262Updated 2 years ago
- Code for the paper "When to Trust Your Model: Model-Based Policy Optimization"☆508Updated 2 years ago
- [NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.☆845Updated last year
- Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...☆415Updated 4 years ago
- Dream to Control: Learning Behaviors by Latent Imagination☆552Updated 4 years ago
- Prioritized Experience Replay (PER) implementation in PyTorch☆351Updated 5 years ago
- Library for Model Based RL☆1,016Updated last year
- A PyTorch library for building deep reinforcement learning agents.☆651Updated last year
- A collection of multi agent environments based on OpenAI gym.☆614Updated last year
- RAD: Reinforcement Learning with Augmented Data☆411Updated 4 years ago
- Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official imp…☆1,339Updated last year
- CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning☆593Updated 4 years ago
- Real-World RL Benchmark Suite☆354Updated 5 years ago
- Implementation of Efficient Off-policy Meta-learning via Probabilistic Context Variables (PEARL)☆501Updated 2 years ago
- Mirror of Stable-Baselines: a fork of OpenAI Baselines, implementations of reinforcement learning algorithms☆302Updated 2 years ago
- A library for ready-made reinforcement learning agents and reusable components for neat prototyping☆300Updated last year
- Structural implementation of RL key algorithms☆514Updated 2 years ago
- List of competitions related to Reinforcement Learning☆349Updated last year
- Code for conservative Q-learning☆454Updated 3 years ago
- High throughput synchronous and asynchronous reinforcement learning☆934Updated 3 months ago
- Dream to Control: Learning Behaviors by Latent Imagination☆657Updated 5 years ago
- Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO☆205Updated 2 years ago