cjm715 / mgym
A collection of multi-agent reinforcement learning OpenAI gym environments
☆44Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for mgym
- ☆97Updated last year
- Pytorch implementation of "FeUdal Networks for Hierarchical Reinforcement Learning" for Montezuma's Revenge☆93Updated 2 years ago
- Hindsight Experience Replay - Bit flipping experiment in Tensorflow☆58Updated 6 years ago
- A library of probabilistic model based RL algorithms in pytorch☆107Updated 3 years ago
- The Reinforcement-Learning-Related Papers of ICLR 2019☆48Updated 5 years ago
- Hierarchical Self-Play☆21Updated 5 years ago
- A Tensorflow implementation of the Option-Critic Architecture☆70Updated 7 years ago
- Deep Reinforcement Learning algorithms implemented in PyTorch☆49Updated 6 years ago
- Code for "Divide-and-Conquer Reinforcement Learning"☆60Updated 5 years ago
- MetaGenRL, a novel meta reinforcement learning algorithm. Unlike prior work, MetaGenRL can generalize to new environments that are entire…☆66Updated 4 years ago
- DHER: Hindsight Experience Replay for Dynamic Goals (ICLR-2019)☆66Updated 5 years ago
- ☆81Updated 3 years ago
- OpenAI Gym Wrapper for DeepMind Control Suite☆71Updated 2 years ago
- This is the pytorch implementation of ICML 2018 paper - Self-Imitation Learning.☆66Updated 6 years ago
- Deep Variational Reinforcement Learning☆134Updated 2 years ago
- Simple grid-world environment compatible with OpenAI-gym☆49Updated 4 years ago
- ☆90Updated 11 months ago
- A comparison of parameter space noise methods for exploration in deep reinforcement learning☆27Updated 5 years ago
- Modifiable OpenAI Gym environments for studying generalization in RL☆86Updated 5 years ago
- Code for "Calibrated Model-Based Deep Reinforcement Learning", ICML 2019.☆55Updated 5 years ago
- Deep Recurrent Attention Reinforcement Learning in Atari☆82Updated 6 years ago
- Adversarial Imitation Via Variational Inverse Reinforcement Learning☆95Updated 4 years ago
- ☆71Updated 5 years ago
- (Experimental) Inverse reinforcement learning from trajectories generated by multiple agents with different (but correlated) rewards☆26Updated 5 years ago
- ☆47Updated 4 years ago
- ☆53Updated 6 years ago
- ☆35Updated 6 years ago
- TD3, SAC, IQN, Rainbow, PPO, Ape-X and etc. in TF1.x☆62Updated 3 years ago
- Simple tools for statistical analyses in RL experiments☆66Updated 6 years ago