A car soccer environment inspired by Rocket League for deep reinforcement learning experiments in an adversarial self-play setting.
-
Updated
Feb 8, 2021 - C#
A car soccer environment inspired by Rocket League for deep reinforcement learning experiments in an adversarial self-play setting.
🤖 Creation of an RL environment with Unity, where an agent must learn to survive by moving 🦿 and shooting🔫, using ML-Agents !
Twin-stick shooter simulation using reinforcement learning in Unity
Multi-Agent-RL Competition on Unitys Tennis Environment
Contains code for Udacity's Deep Reinforcement learning Nanodegree program. The projects consist of experiments and implementations of DQN and DDPG algorithms using PyTorch, OpenAI Gym and UnityML Agents.
bachelors Main Project- Planes understand path/Track via Machine Learning
Citizen Science (Sci-tizen) visualisation in the Unity.com engine
Project 1 of Udacity Deep Reinforcement Learning Nanodegree
Reinforcement learning project using unity, 2 agents learn to play catch.
Add a description, image, and links to the unityml topic page so that developers can more easily learn about it.
To associate your repository with the unityml topic, visit your repo's landing page and select "manage topics."