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

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).

☔ Deep RL agents with PyTorch☔

Some model free RL algorithms

Minimal Implementation of Deep RL Algorithms in PyTorch

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

ROS 2 enabled Machine Learning algorithms

ROS 2 enabled Machine Learning algorithms

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

Handmade environments and trained models.

Implementation of A2C and ACKTR in TensorFlow.

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)

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