autonomous-learning-library
DRL framework
A comprehensive library for building deep reinforcement learning agents using PyTorch
A PyTorch library for building deep reinforcement learning agents.
647 stars
23 watching
72 forks
Language: Python
last commit: 11 months ago a2cadvantage-actor-criticddpgdeep-deterministic-policy-gradientdeep-q-learningdeep-reinforcement-learningdqndqn-pytorchppoproximal-policy-optimizationreinforcement-learningreinforcement-learning-algorithmssacsoft-actor-critic
Related projects:
Repository | Description | Stars |
---|---|---|
| A comprehensive project that provides an implementation of deep reinforcement learning algorithms using PyTorch and Visdom. | 798 |
| An open-source reinforcement learning library for PyTorch, providing a simple and clear implementation of various algorithms. | 402 |
| A comprehensive framework for deep reinforcement learning using PyTorch. | 1,256 |
| Replication of Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks in PyTorch for reinforcement learning tasks | 830 |
| An implementation of reinforcement learning algorithms for continuous control tasks using deep neural networks. | 307 |
| A JavaScript library that provides GPU-accelerated deep learning capabilities with automatic differentiation and neural network layers. | 1,093 |
| A modular and unified framework for implementing common deep reinforcement learning algorithms in PyTorch | 2,236 |
| This project implements a PyTorch-based framework for learning discrete communication protocols in multi-agent reinforcement learning environments. | 349 |
| Trains an RL agent to execute natural language instructions in a 3D environment using a combination of A3C and gated attention mechanisms. | 237 |
| A PyTorch-based toolbox for building and training deep learning models with ease. | 204 |
| A PyTorch framework simplifying neural network training with automated boilerplate code and callback utilities | 572 |
| A PyTorch framework for accelerating reinforcement learning research and development by providing a modular, reusable, and customizable training loop | 46 |
| An implementation of reinforcement learning algorithm using PyTorch and designed to work with Atari games. | 96 |
| An implementation of a deep reinforcement learning network using PyTorch to learn human-level control through trial and error. | 387 |
| A high-performance implementation of reinforcement learning training pipelines using JAX and PyTorch-like functionality | 755 |