harvard-edge / QuaRLLinks
QuaRL is an open-source framework for systematically studying the effect of applying quantization to reinforcement learning algorithms.
β72Updated 2 years ago
Alternatives and similar repositories for QuaRL
Users that are interested in QuaRL are comparing it to the libraries listed below
Sorting:
- π§Ά Minimal PyTorch Soft Actor Critic (SAC) implementationβ39Updated 3 years ago
- Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020β32Updated 4 years ago
- PyTorch implementation of our paper Real-Time Reinforcement Learning (NeurIPS 2019)β74Updated 5 years ago
- Datasets for data-driven deep reinforcement learning with PyBullet environmentsβ150Updated 4 years ago
- PyTorch implementation of Stochastic Latent Actor-Critic(SLAC).β93Updated last year
- Implementation of the Model-Based Meta-Policy-Optimization (MB-MPO) algorithmβ44Updated 6 years ago
- Revisiting Rainbowβ75Updated 4 years ago
- Implicit Normalizing Flows + Reinforcement Learningβ61Updated 6 years ago
- Pytorch implementation of Soft Actor-Criticβ20Updated 5 years ago
- PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learningβ49Updated 4 years ago
- Continual Reinforcement Learning in 3D Non-stationary Environmentsβ38Updated 6 years ago
- This code implements Prioritized Level Replay, a method for sampling training levels for reinforcement learning agents that exploits the β¦β88Updated 4 years ago
- Automatic Data-Regularized Actor-Critic (Auto-DrAC)β102Updated 2 years ago
- SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learningβ127Updated 4 years ago
- Pytorch implementation of "FeUdal Networks for Hierarchical Reinforcement Learning" for Montezuma's Revengeβ96Updated 3 years ago
- β111Updated 5 years ago
- Implementation of Bootstrap DQN and Randomized Prior Functions on ALEβ54Updated 4 months ago
- Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.β114Updated 4 years ago
- PyTorch implementation of the Munchausen Reinforcement Learning Algorithms M-DQN and M-IQNβ45Updated 4 years ago
- Proximal policy optimization in PyTorch. Easy to read and understand.β50Updated 4 years ago
- MultiTask Environments for Reinforcement Learning.β76Updated 2 years ago
- Multi Task RL Baselinesβ246Updated 3 years ago
- Pytorch implementation of distributed deep reinforcement learningβ76Updated 3 years ago
- IV-RL - Sample Efficient Deep Reinforcement Learning via Uncertainty Estimationβ40Updated 3 weeks ago
- Estimating Q(s,s') with Deep Deterministic Dynamics Gradientsβ32Updated 5 years ago
- Code for our NeurIPS 2020 paper Improving Generalization in Reinforcement Learning with Mixture Regularizationβ33Updated 4 years ago
- Combining Evolutionary Algorithms and deep RL in various waysβ103Updated 4 years ago
- Codes for the study "Variational Recurrent Models for Solving Partially Observable Control Tasks", published as a conference paper at ICLβ¦β55Updated 4 years ago
- β72Updated 2 years ago
- on-policy optimization baselines for deep reinforcement learningβ30Updated 5 years ago