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ML-Lander

Made with Unity Machine Learning Agents Toolkit

This project was done within the scope of the Machine Learning curricular unit.

FACULTY

Ana Maria de Almeida

Luís Nunes

Master in Computer Engineering

ISCTE - University of Lisbon 2018

iscte-iul.pt

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source Unity plugin that enables games and simulations to serve as environments for training intelligent agents. Agents can be trained using reinforcement learning, imitation learning, neuroevolution, or other machine learning methods through a simple-to-use Python API. We also provide implementations (based on TensorFlow) of state-of-the-art algorithms to enable game developers and hobbyists to easily train intelligent agents for 2D, 3D and VR/AR games. These trained agents can be used for multiple purposes, including controlling NPC behavior (in a variety of settings such as multi-agent and adversarial), automated testing of game builds and evaluating different game design decisions pre-release. The ML-Agents toolkit is mutually beneficial for both game developers and AI researchers as it provides a central platform where advances in AI can be evaluated on Unity’s rich environments and then made accessible to the wider research and game developer communities.

Documentation

  • For more information, in addition to installation of Unity ML-Agents, see documentation home.

Relevant articles:

License

Apache License 2.0

References

Juliani, A., Berges, V., Vckay, E., Gao, Y., Henry, H., Mattar, M., Lange, D. (2018). Unity: A General Platform for Intelligent Agents. arXiv preprint arXiv:1809.02627. https://github.com/Unity-Technologies/ml-agents.

Minimal Cartoon Rocketship 3D model by Gambsmoore https://poly.google.com/view/dsjkFYy-rb0 , available under a Creative Commons Attribution-Noncommercial license.