Everything You Need To Know About Machine Learning In Unity 3D – Analytics India Magazine

Unity 3D is a popular platform for creating and operating interactive, real-time 3D content. It is a cross-platform 3D engine and a user-friendly integrated development environment (IDE) which helps in creating games in 3D as well as applications for desktop, mobile, web and more. It consists of a number of tools for programmers as well as artists to create real-time solutions, such as films and automotive, apart from games. The flexible real-time tools of Unity offer incredible possibilities for all industries and applications.

With a vision to maximise the transformative impact of Machine Learning for researchers and developers, Unity released the first version of Unity Machine Learning Agents Toolkit (ML-Agents) in 2017.

The aim of this ML environment is to allow game developers and AI researchers to use Unity as a platform to train as well as embed intelligent agents with the help of the latest advancements in ML and AI.

The Unity Machine Learning Agents Toolkit or simply ML-Agents is an open-source project by Unity, which allows games and simulations to serve as environments for training the intelligent agents. ML-Agents includes a C# software development kit (SDK) to set up a scene and define the agents within it, and a state-of-the-art ML library to train agents for 2D, 3D, and VR/AR environments.

The agents can be trained using techniques like reinforcement learning, imitation learning, neuro-evolution and other such ML methods through a simple-to-use Python API. The toolkit includes a number of training options, such as Curriculum Learning, Curiosity module for sparse-reward environments, Self-Play for multi-agent scenarios and more.

The Unity environment also provides implementations of state-of-the-art algorithms, which are based on TensorFlow to enable game developers to easily train intelligent agents for 2D, 3D and VR/AR games.

These trained agents can be utilised for multiple purposes, including controlling NPC behaviour, automated testing of the game builds as well as evaluating various game design decisions prior to its release.

The ML-Agents Toolkit provides a central platform where advances in Artificial Intelligence can be evaluated on the environments of Unity and then made accessible to the game developer communities for wider research.

Unity ML-Agents include a number of intuitive features. Some of them are:

Unity Machine Learning Agents (ML-Agents) allows developers to create more compelling gameplay and enhanced game experience. Using the platform, a developer can teach intelligent agents to learn through a combination of deep reinforcement learning and imitation learning.

The steps involved in ML-Agents are:

Know more here.

The key benefits of Unity ML-Agents are:

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A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box. Contact: ambika.choudhury@analyticsindiamag.com

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Everything You Need To Know About Machine Learning In Unity 3D - Analytics India Magazine