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).

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

ROS 2 enabled Machine Learning algorithms

☔ Deep RL agents with PyTorch☔

Minimal Implementation of Deep RL Algorithms in PyTorch

Distributed Online Service Coordination Using Deep Reinforcement Learning

Deep reinforcement learning framework for fast prototyping based on PyTorch

Exhaustive Implementation of Algorithms, Key Papers, and Well-Known Problems of Reinforcement Leaning

Interfacing RL agents with user-definable neural networks and OpenAI-gym environments.

Implementation of A2C and ACKTR in TensorFlow.

Teaching a neural network how to write letters and digits with reinforcement learning.

Some model free RL algorithms

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO) and Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR). Python2 compatible (branch python2)

Handmade environments and trained models.

ROS 2 enabled Machine Learning algorithms