ml-agents and A.I.-Jumping-Cars-ML-Agents-Example
ML-Agents is the foundational reinforcement learning framework that Jumping-Cars uses as a dependency to demonstrate practical agent training within Unity3D, making them complementary tools rather than alternatives.
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.-Jumping-Cars-ML-Agents-Example
Sebastian-Schuchmann/A.I.-Jumping-Cars-ML-Agents-Example
Ultimate Walkthrough Example for ML-Agents 1.0+ in Unity3D
This project provides a comprehensive guide for game developers and AI enthusiasts to integrate Unity’s ML-Agents with Unity3D. It helps you transform player characters into intelligent agents capable of learning complex behaviors, such as dodging obstacles. By following the steps, you can train AI to perform actions, using input like distance to obstacles and outputting discrete actions like 'jump' or 'do nothing'.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work