Package Versions

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

Package	Version
com.unity.ml-agents (C#)	v2.2.1-exp.1
com.unity.ml-agents.extensions (C#)	v0.6.1-preview
ml-agents (Python)	v0.28.0
ml-agents-envs (Python)	v0.28.0
gym-unity (Python)	v0.28.0
Communicator (C#/Python)	v1.5.0

Release Notes

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)

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)

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)

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)

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)