A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

Deep Reinforcement Learning for Trading

Actor Critic using Kronecker-Factored Trust Region

Solving CartPole-v1 environment in Keras with Actor Critic algorithm an Deep Reinforcement Learning algorithm

Official repository for the paper "Exploring the Promise and Limits of Real-Time Recurrent Learning" (ICLR 2024)

Design and training of an RL agent to control a Quadcopter using Actor-Critic RL method

a collection of python notebooks using RL agents to play Atari games in OpenAI gym environments

Topics in Machine Learning @ IIIT Hyderabad (Fall 2021)

Deep Reinforcement Learning: Continuous Control. Solve the Unity ML-Agents Reacher Environment.

Objective Stimuli Active Repeater

Implementations of some of the most well known Deep Reinforcement Learning algorithms

This repository contains high quality and tested implementation of Asynchronous Actor Critic Algorithm

Projects and Exercises of Udacity Deep Reinforcement Learning Nanodegree

A model to control a double-jointed arm to reach target using Deep Deterministic Policy Gradients

Implemented the Actor-Critic method using TensorFlow to train an agent on the Open AI Gym CartPole-V0 environment.

Fun with Reinforcement Learning in my spare time

Programming Assignments for Reinforcement Learning Specialization

Deep Reinforcement Learning: On-Policy Actor Critic methods. An implementation of Advantage Actor-Critic (A2C) and Proximal Policy Optimization (PPO) on the PyTorch Lightning framework.

unRL (AKA "unreal") is a set of libraries providing Reinforcement Learning algorithms implemented in PyTorch or Jax.