The ML-Agents Toolkit allows researchers and game developers to build and train agents in Unity environments using Reinforcement Learning (RL). RL is useful when it is easier to specify what task an agent needs to complete rather than how to do it. An agent learns to select actions to complete a task on its own using observations from its environment and a task reward signal. Here’s how our interns improved our RL and ML-agents this summer.

We recently published two blog posts, Five ways to speed up your workflows in the Editor and Speed up your artist workflows, both based on our e-book for professional developers, 70+ tips to increase productivity with Unity 2020 LTS. In this third and final blog post in the series, we focus on workflows and the features that help programmers get more done in less time. Let’s start with how you can save compilation time when playtesting.

While implementing your first version control system or moving to a new one can be challenging, the long-term impact is worth it. Here’s what to consider when choosing a version control system, before you commit.

  Unity is excited to announce our official support of ROS 2, whose robust framework, […]