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ECS features in detail Note: The main content of this page has migrated to the Unity Data-Oriented reference. ECS related features are listed below in alphabetical order, with a short description and links to further information about it. This page is not an exhaustive list and can be added to over time as ECS, and its related documentation expands. If you spot something that is out-of-date or bro
Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Sign up Getting Started with the 3D Balance Ball Environment This tutorial walks through the end-to-end process of opening a ML-Agents toolkit example environment in Unity, building the Unity executable, training an Agent in it, and finally
Unity Data-Oriented Tech Stack Manual This manual covers the three main aspects of Unity's Data-Oriented Tech Stack: Entity-Component-System (ECS), C# Job System, and Burst. Table of contents Entity-Component-System overview C# Job System overview Burst overview Tutorials Examples Community Further information, including: Data-Oriented cheat sheet Data-Oriented reference Entity-Component-System ov
Best Practices when training with PPO The process of training a Reinforcement Learning model can often involve the need to tune the hyperparameters in order to achieve a level of performance that is desirable. This guide contains some best practices for tuning the training process when the default parameters don't seem to be giving the level of performance you would like. Hyperparameters Batch Siz
We are changing how we develop additional 2D Tiles and Brushes for 2D Tilemap. An important part of this change involves ensuring a single point of entry for users to get the latest tiles and brushes for Tilemap. To this end we created the Tilemap Extras package which is accessible from Package Manager. Moving forward, the 2D-extras GitHub repository will be made read-only. You will still be able
(latest release) (all releases) 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. We provide implementations (based on PyTorch) of state-of-the-art algorithms to enable game developers and hobbyists to easily train intelligent agents for 2D, 3D and VR/AR games. Researchers can
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