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AutoParkAI

An AI agent that learns to park a vehicle in a vertical parking spot using Reinforcement Learning.

Overview

This project aimed to develop an AI agent capable of learning to park a vehicle in a vertical parking spot using Reinforcement Learning. The agent was trained in a simulated environment using the Proximal Policy Optimization (PPO) algorithm and the Unity ML-Agents toolkit.

Features

  • AI Parking Agent: The agent learns to park a vehicle in a vertical parking spot.
  • Reinforcement Learning: The agent is trained using the Proximal Policy Optimization (PPO) algorithm.
  • Unity ML-Agents: The agent is developed using the Unity ML-Agents toolkit.

Technologies

  • Programming Languages: C#
  • Libraries: Unity ML-Agents
  • Tools: Unity