Implementation of Proximal Policy Optimization algorithm on a custom Unity environment.

Implementation of project 3 for Udacity's Deep Reinforcement Learning Nanodegree

An implementation of MADDPG multi-agent to solve a Unity environment like Tennis and Soccer.

An unofficial library for interacting with Discord Webhook aimed at use in the Unity environment

Implementation of project 2 for Udacity's Deep Reinforcement Learning Nanodegree

We train an agent to manuver in a 3-D environment avoiding blue bananas and picking yellow ones as fast as possible.

Deep Reinforcement Learning Projects

This is the 2nd project in Udacity DRLND, which is practice for training an agent that controls a robotic arm in Unity's Reacher environment using the Deep Deterministic Policy Gradients (DDPG) algorithm.

Create and train a double-jointed arm agent that is able to maintain its hand in contact with a moving target

Implementation of project 1 for Udacity's Deep Reinforcement Learning Nanodegree

Multiagent RL

Collaboration and Competition (using multi agent reinforcement learning). Train a pair of agents to play tennis.

Deep reinforcement Learning Nanodegree - Navigation Project

Solving Reacher environment using deep reinforcement learning

Training an agent to perform continuous task

Train double-jointed arms to reach target locations using Proximal Policy Optimization (PPO) in Pytorch

Solution of a first project of the deep reinforcement learning nanodegree at Udacity.

An implementation of Deep Q-Learning Network for solving a Unity environment that can navigate and collect bananas in a large, square world.