Package Versions

NOTE: It is strongly recommended that you use packages from the same release together for the best experience.

Release Notes

Major Changes

com.unity.ml-agents / com.unity.ml-agents.extensions (C#)

• The minimum supported Unity version was updated to 2020.3. (#5673)
• Added a new feature to replicate training areas dynamically during runtime. (#5568)
• Update Barracuda to 2.3.1-preview (#5591)
• Update Input System to 1.3.0 (#5661)

ml-agents / ml-agents-envs / gym-unity (Python)

Minor Changes

com.unity.ml-agents / com.unity.ml-agents.extensions (C#)

• Added the capacity to initialize behaviors from any checkpoint and not just the latest one (#5525)
• Added the ability to get a read-only view of the stacked observations (#5523)

ml-agents / ml-agents-envs / gym-unity (Python)

• Set gym version in gym-unity to gym release 0.20.0 (#5540)
• Added support for having beta, epsilon, and learning rate on separate schedules (affects only PPO and POCA). (#5538)
• Changed default behavior to restart crashed Unity environments rather than exiting. (#5553)
  • Rate & lifetime limits on this are configurable via 3 new yaml options
    1. env_params.max_lifetime_restarts (--max-lifetime-restarts) [default=10]
    2. env_params.restarts_rate_limit_n (--restarts-rate-limit-n) [default=1]
    3. env_params.restarts_rate_limit_period_s (--restarts-rate-limit-period-s) [default=60]
• Deterministic action selection is now supported during training and inference(#5619)
  • Added a new --deterministic cli flag to deterministically select the most probable actions in policy. The same thing can
    be achieved by adding deterministic: true under network_settings of the run options configuration.(#5597)
  • Extra tensors are now serialized to support deterministic action selection in onnx. (#5593)
  • Support inference with deterministic action selection in editor (#5599)
• Added minimal analytics collection to LL-API (#5511)
• Update Colab notebooks for GridWorld example with DQN illustrating the use of the Python API and how to export to ONNX (#5643)

Bug Fixes

com.unity.ml-agents / com.unity.ml-agents.extensions (C#)

• Update gRPC native lib to universal for arm64 and x86_64. This change should enable ml-agents usage on mac M1 (#5283, #5519)
• Fixed a bug where ml-agents code wouldn't compile on platforms that didn't support analytics (PS4/5, XBoxOne) (#5628)

ml-agents / ml-agents-envs / gym-unity (Python)

• Fixed a bug where the critics were not being normalized during training. (#5595)
• Fixed the bug where curriculum learning would crash because of the incorrect run_options parsing. (#5586)
• Fixed a bug in multi-agent cooperative training where agents might not receive all of the states of
  terminated teammates. (#5441)
• Fixed wrong attribute name in argparser for torch device option (#5433)(#5467)
• Fixed conflicting CLI and yaml options regarding resume & initialize_from (#5495)
• Fixed failing tests for gym-unity due to gym 0.20.0 release (#5540)
• Fixed a bug in VAIL where the variational bottleneck was not properly passing gradients (#5546)
• Harden user PII protection logic and extend TrainingAnalytics to expose detailed configuration parameters. (#5512)