ML-Agents Beta 0.2

Environments

• Four new example environments added (learn more):

  • Crawler
  • Reacher
  • Wall Area
  • Push Area

• Environments no longer use normalized state values due to optional auto-normalizing done in PPO.

Features

Communication API Updated. Be sure both Unity project files and Python api are most current version.

Python

• PPO now optionally auto-normalizes states using running-average and running-variance (with --normalize flag).
• unityagents package now includes Curriculum Learning support (learn more).
• Absolute path to training environments can now be used when running UnityEnvironment().
• The Environment now logs errors and exceptions on the Unity side into the unity-environment.log file.

Unity

• New more flexible Monitor which allows for displaying arbitrary information (learn more).
• Broadcast support for internal, heuristic, and player brains which allows all relevant agent information to be sent to python-side for supervised/imitation learning (learn more).

Bug Fixes & Performance Improvements

Python

• Communication code now supports arbitrarily large observation cameras and states.

Unity

• Cumulative reward now accurately tracks reward.
• AcademyReset() now called before agent reset.
• isInference is now correctly set when running in Editor.
• Frame-rate is unlocked by default when in isInference is false.