Unity ML-Agents

Unity ML-Agents Toolkit

(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 also use the provided simple-to-use Python API to train Agents using reinforcement learning, imitation learning, neuroevolution, or any other methods. 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.

Features
- 17+ example Unity environments
- Support for multiple environment configurations and training scenarios
- Flexible Unity SDK that can be integrated into your game or custom Unity scene
- Support for training single-agent, multi-agent cooperative, and multi-agent competitive scenarios via several Deep Reinforcement Learning algorithms (PPO, SAC, MA-POCA, self-play).
- Support for learning from demonstrations through two Imitation Learning algorithms (BC and GAIL).
- Quickly and easily add your own custom training algorithm and/or components.
- Easily definable Curriculum Learning scenarios for complex tasks
- Train robust agents using environment randomization
- Flexible agent control with On Demand Decision Making
- Train using multiple concurrent Unity environment instances
- Utilizes the Inference Engine to provide native cross-platform support
- Unity environment control from Python
- Wrap Unity learning environments as a gym environment
- Wrap Unity learning environments as a PettingZoo environment

Releases & Documentation

> ⚠️ Documentation Migration Notice
> We have moved to Unity Package documentation as the primary developer documentation and have deprecated the maintenance of web docs. Please use the Unity Package documentation for the most up-to-date information.

The table below shows our latest release, including our develop branch which is under active development and may be unstable. A few helpful guidelines:

- The Versioning page overviews how we manage our GitHub releases and the versioning process for each of the ML-Agents components.
- The Releases page contains details of the changes between releases.
- The Migration page contains details on how to upgrade from earlier releases of the ML-Agents Toolkit.
- The com.unity.ml-agents package is verified for Unity 2020.1 and later. Verified packages releases are numbered 1.0.x.

|      Version       |  Release Date   |                                  Source                                   |                                                 Documentation

……（后略，见原文）