An elegant PyTorch deep reinforcement learning library.
-
Updated
Aug 18, 2024 - Python
An elegant PyTorch deep reinforcement learning library.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning Deep Learning
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
Massively Parallel Deep Reinforcement Learning. 🔥
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
Modularized Implementation of Deep RL Algorithms in PyTorch
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".
PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
A PyTorch library for building deep reinforcement learning agents.
RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Add a description, image, and links to the a2c topic page so that developers can more easily learn about it.
To associate your repository with the a2c topic, visit your repo's landing page and select "manage topics."