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MindMaker Machine Learning AI Plugin

Aaron Krumins - Code Plugins - Nov 6, 2020

AI Plugin that enables a variety of python based Machine Learning libraries within Unreal Engine

  • Supported Platforms
  • Supported Engine Versions
  • Download Type
    Engine Plugin
    This product contains a code plugin, complete with pre-built binaries and all its source code that integrates with Unreal Engine, which can be installed to an engine version of your choice then enabled on a per-project basis.

Video: https://youtu.be/ERm_pZhAPIA

Github Documentation: https://github.com/krumiaa/MindMaker

The MindMaker AI Plugin is an open-source plugin that enables games and simulations within UE4 to function as environments for training autonomous machine learning agents. The plugin facilitates a network connection between an Unreal Project containing the learning environment, and a standalone machine learning library used by the agent to optimize whatever it is attempting to learn. The standalone machine learning library can either be a custom python script in the event you are creating your own ML tool using MindMaker’s Remote ML Server, or it could be a precompiled learning engine such as MindMaker’s DRL Engine(Stable Baselines Algorithms). Regardless of which option you choose, with the MindMaker AI Plugin developers and researchers can easily train machine learning agents for 2D, 3D and VR projects.

Use cases include robotic simulation, autonomous driving, generative architecture, procedural graphics and much more. MindMaker AI Plugin provides a central platform from which advances in machine learning can reach many of these fields. For game developers, the use cases for self-optimizing agents include controlling NPC behavior, prototyping game design decisions, and automated testing of game builds.

Algorithms supported include Stable Baselines : Actor Critic ( A2C ), Sample Efficient Actor-Critic with Experience Replay (ACER), Actor Critic using Kronecker-Factored Trust Region ( ACKTR ), Deep Q Network ( DQN ), Proximal Policy Optimization ( PPO ), Soft Actor Critic ( SAC ), Twin Delayed DDPG ( TD3 )

Technical Details


  • Implement python based ML libraries directly in Unreal Engine with the MindMaker Client Server files – See RemoteML Example and Documentation
  • Precompiled Deep Reinforcement Learning Package for production use cases – auto-launches at start of game / simulation
  • Github Support - https://github.com/krumiaa/MindMaker
  • Modular Design for Easy Integration
  • Direct Access to Neural Networks via Blueprints
  • Three Example Projects Included

Code Modules:

  • MindMakerBPLibrary - Developer, CoreUtility - Runtime, SIOJson - Runtime, SocketIOClient - Runtime, SIOJEditorPlugin – Developer,

Number of Blueprints: 0

Number of C++ Classes: 18

Network Replicated: No

Supported Development Platforms: Win64

Supported Target Build Platforms: Win64

Documentation: http://www.autonomousduck.com/plugin.html


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Example Project: https://drive.google.com/file/d/1Bs7mVUCt5G3-sBDFPe8oZCv5GZC4V7cj/view?usp=sharing

Important/Additional Notes: Download Learning Engine and Starter Content