ml-agents and A.I.-Shooting-Game-ML-Agents-Unity-Example
ML-Agents is the core framework that Sebastian-Schuchmann's project extends as a beginner-friendly tutorial demonstrating practical implementation of the toolkit's reinforcement learning capabilities.
About ml-agents
Unity-Technologies/ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
This toolkit helps game developers and researchers create intelligent characters and systems within Unity games and simulations. You provide a Unity game environment, and the toolkit outputs trained AI agents that can control Non-Player Characters (NPCs), automate game testing, or evaluate design choices. Game developers and AI researchers are the primary users.
About A.I.-Shooting-Game-ML-Agents-Unity-Example
Sebastian-Schuchmann/A.I.-Shooting-Game-ML-Agents-Unity-Example
A beginner friendly example for Unity's ML-Agents Framework. This project teaches you how to train an A.I. via Machine Learning.
This project helps game developers and hobbyists learn how to integrate machine learning into Unity games. It takes a Unity game environment and allows you to train an AI agent to perform tasks, ultimately producing an AI that can play the game. Anyone looking to add intelligent behaviors to game characters using ML-Agents in Unity would find this useful.
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