Questo progetto Unity utilizza ML-Agents (PPO) per addestrare un agente veicolare in una città appartenente al pacchetto di SyntyStudios POLYGON - City Pack. L'agente cerca di: Schivare i gatti; seguire la segnaletica orizzontale; mantenere la corsia di sinistra; effettuare parcheggi nel punto di interesse più vicino.

Use of reinforcement learning with PPO to train an Agent that can beat the first level of Donkey Kong

Deep Reinforcement Learning in C#

Reinforcement Learning - Route Optimization with Unity - ML-agents

Target Strike game is an unity based compititive game. This game is created for CS662 - Mobile VR & AI course offered at IIT Mandi. Here the source files are given.

research - multi-agent car parking using reinforcement learning

Car game made with unity

Final task for my Reinforcement Learning class in Deusto. The research paper discuss examples of using ML-Agents toolkit of Unity. Paper is avaible at:

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Simulation of car parking in different parking lots using Unity ML-Agents

A car agent that has been trained using reinforcement learning to complete successful laps on a scaled-down version of the Circuit de Barcelona-Catalunya.

Proyecto de entrenamiento de modelos de IA con aprendizaje por refuerzo (reinforcement learning) en Unity. Corresponde al trabajo práctico grupal de la materia INTELIGENCIA ARTIFICIAL (9525) de la Facultad de Ingeniería de la Universidad de Buenos Aires. Link a la demo (el comportamiento de los agentes puede verse afectado de forma negativa):

An implementation of the Proximal Policy Optimization (PPO) algorithm. This implementation is based on the example available on the official Keras website. The goal of this project is to provide a .NET-based solution for running PPO algorithms.

Unity Environments based on ML-agents for the Walker agent to perform various locomotion behaviors using reinforcement learning

A simple demo showing asteroids with ML-Agents

Deep Reinforcement Learning techniques (PPO) applied to Swarm Robotics, focusing on defining stimulating environments and communication patterns in Search and Rescue scenario

Rocket landing AI using reinforcement learning [keyword][Reinforcement Learning, ppo algorithm, ML-Agent]

Concept and development of a walking AT-ST Walker (Starwars) ML-agent.

My master's degree project, titled Quadcopter Control with Deep Reinforcement Learning and PID Controllers in Simulated Environments

A comparison between Reinforcement and Imitation Learning techniques for Multi-Agent 3D Racing using sensor-based approaches.