microsoft / FQFLinks
FQF(Fully parameterized Quantile Function for distributional reinforcement learning) is a general reinforcement learning framework for Atari games, which can learn to play Atari games automatically by predicting return distribution in the form of a fully parameterized quantile function.
☆47Updated 5 years ago
Alternatives and similar repositories for FQF
Users that are interested in FQF are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of distributed deep reinforcement learning☆76Updated 3 years ago
- PyTorch implementation of FQF, IQN and QR-DQN.☆188Updated last year
- Code for the paper "Phasic Policy Gradient"☆267Updated 2 years ago
- A Modular Library for Off-Policy Reinforcement Learning with a focus on SafeRL and distributed computing☆137Updated 5 months ago
- Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO☆205Updated 3 years ago
- Code for 'Dynamics-Aware Unsupervised Discovery of Skills' (DADS). Enables skill discovery without supervision, which can be combined wit…☆193Updated 4 years ago
- Modified versions of the SAC algorithm from spinningup for discrete action spaces and image observations.☆99Updated 5 years ago
- PyTorch implementation of Stochastic Latent Actor-Critic(SLAC).☆94Updated last year
- SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning☆130Updated 4 years ago
- Code for "Data-Efficient Reinforcement Learning with Self-Predictive Representations"☆163Updated 4 years ago
- Keeping track of RL experiments☆166Updated 3 years ago
- PyTorch Implementation of Distributed Prioritized Experience Replay(Ape-X)☆155Updated 6 years ago
- Random Network Distillation pytorch☆260Updated 6 years ago
- Code accompanying the paper "Better Exploration with Optimistic Actor Critic" (NeurIPS 2019)☆69Updated 2 years ago
- Arena: A General Evaluation Platform and Building Toolkit for Single/Multi-Agent Intelligence. AAAI 2020.☆84Updated 4 years ago
- Datasets for data-driven deep reinforcement learning with PyBullet environments☆152Updated 4 years ago
- Implementation of VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning - Zintgraf et al. (ICLR 2020)☆198Updated 2 years ago
- Unofficial Pytorch code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"☆194Updated 3 years ago
- pytorch-implementation of Dreamer (Model-based Image RL Algorithm)☆168Updated last year
- Soft Actor-Critic☆157Updated 7 years ago
- OpenAI Gym wrapper for the DeepMind Control Suite☆226Updated last year
- Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model☆154Updated 5 years ago
- ☆148Updated last year
- Soft Actor-Critic with advanced features☆51Updated last month
- ☆202Updated 2 years ago
- Random network distillation on Montezuma's Revenge and Super Mario Bros.☆54Updated 8 months ago
- This repository contains the code to implement the Hierarchical Actor-Critic (HAC) algorithm.☆269Updated 5 years ago
- A framework for easy prototyping of distributed reinforcement learning algorithms☆96Updated 5 years ago
- Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM)☆147Updated 7 years ago
- An implement of DQfD(Deep Q-learning from Demonstrations) raised by DeepMind:Learning from Demonstrations for Real World Reinforcement Le…☆132Updated 8 years ago