ml-agents and UnrealMLAgents

ML-Agents is a direct competitor that provides the same reinforcement learning training framework functionality, but UnrealMLAgents is a specialized port attempting to replicate that capability for Unreal Engine rather than Unity, making them mutually exclusive choices for the same use case depending on which game engine you're using.

ml-agents
70
Verified
UnrealMLAgents
40
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 25/25
Community 25/25
Maintenance 2/25
Adoption 9/25
Maturity 16/25
Community 13/25
Stars: 19,215
Forks: 4,431
Downloads:
Commits (30d): 0
Language: C#
License:
Stars: 75
Forks: 9
Downloads:
Commits (30d): 0
Language: Python
License:
No risk flags
Stale 6m No Package No Dependents

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.

game-development AI-research-games NPC-behavior game-testing simulation-training

About UnrealMLAgents

AlanLaboratory/UnrealMLAgents

The Unreal ML Agents Toolkit is an open-source project that enables Unreal Engine games and simulations to serve as environments for training intelligent agents using deep reinforcement learning. This project is a port of Unity ML-Agents, adapted to work within Unreal Engine.

This plugin helps Unreal Engine game developers and simulation creators train AI agents to behave intelligently within their virtual environments. It allows you to define tasks and rewards, then feeds the game state (like agent position and nearby objects) into a machine learning model. The output is an AI agent that learns to perform complex actions through trial and error, making games more dynamic or simulations more realistic.

game-development AI-training simulation Unreal-Engine reinforcement-learning

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