#A2c
Showing 14 of 14 repositories tagged #a2c, ranked by stars
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 ....
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).
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
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)
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
The simplest implementation of Pensieve (SIGCOMM' 17) via state-of-the-art RL algorithms, including PPO, DQN, SAC, and support for both TensorFlow and PyTorch.
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
Portfolio management using Actor-Critic Deep Reinforcement Learning algorithms including A2C, DDPG, and PPO
Deep Reinforcement Learning for Trading