Multi agent PPO implementation in Pytorch for Unity ML Agents environments.

3D Packing with Deep Reinforcement Learning using Unity ML-Agents (AI)

Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM) on Pyramid env, Unity ML

Continuous Control with deep reinforcement learning where the agent must reach a moving ball with a double jointed arm

Train an agent using RL to navigate (and collect bananas) in a large, square world

In this repo, I implement deep deterministic policy gradients and multi-agent deep deterministic poilicy gradients to solve the Tennis enironment (Unity ML-Agents)

Deep Reinforcement Learning: Two Competing Tennis Playing Agents

Keeping the double-jointed arm hand in the green sphere

심층강화학습기반 디지털 트윈 환경에서의 자율주행 연구

Project 2 of Udacity's Deep Reinforcement Learning Nanodegree Program

Deep Reinforcement Learning: Navigation. Capture yellow bananas while avoiding blue bananas with an agent trained using Deep Q-Networks on a Unity ML-Agent environment.

Some of my solutions of the exercises and all my projects of the Udacity Deep Reinforcement Learning Nanodegree https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893

Training a pair of agents to play tennis

Project 1 of Udacity's Deep Reinforcement Learning Nanodegree Program

Small Reinforcement Learning Framework

My solutions to the projects within the Udacity Deep Reinforcement Learning Nanodegree.

Udacity's Reinforcement Learning Project 1

Project 3 of Udacity's Deep Reinforcement Learning Nanodegree Program

Deep Q-Learning Agent mastering the Unity Banana Collector environment! — Udacity Deep RL Nanodegree Project

A pair of reinforcement learning agents that can play tennis 🎾 — Udacity Deep RL Nanodegree Project