* added broadcast to the player and heuristic brain.
Allows the python API to record actions taken along with the states and rewards
* removed the broadcast checkbox
Added a Handshake method for the communicator
The academy will try to handshake regardless of the brains present
Player and Heuristic brains will send their information through the communicator but will not receive commands
* bug fix : The environment only requests actions from external brains when unique
* added warning in case no brins are set to external
* fix on the instanciation of coreBrains,
fix on the conversion of actions to arrays in the BrainInfo received from step
* default discrete action is now 0
bug fix for discrete broadcast action (the action size should be one in Agents.cs)
modified Tennis so that the default action is no action
modified the TemplateDecsion.cs to ensure non null values are sent from Decide() and MakeMemory()
* minor fixes
* need to convert the s...
* Add support for stacking past n states to allow network to learn temporal dependencies.
* Add Banana Collector environment for demonstrating partially observable multi-agent environments.
* Add 3DBall Hard which lacks velocity information in state representation. Used as test for LSTM and state-stacking features.
* Rework Tennis environment to be continuous control and trainable in 100k steps.
This PR makes the following changes:
* Moves clipping of continuous control model into model itself. Output is now always [-1, 1].
* Internal model values are now clipped between [-3, 3] before being rescaled to [-1, 1] for output. * This improves training performance by providing a wider range of values within which the pdf of the gaussian can fall. Output of [-1, 1] is used to be more environment-creator friendly.
* Fixes issue where epsilon was erroneously being used to reconstruct old probabilities during PPO update, leading to reduced learning performance.
* Introduce ScaleAction() function within python to easily rescale values from [-1, 1] to arbitrary range.
* Re-train all CC models using improved algorithm. All performance levels are equal or improved. In the case of Crawler, improvement is drastic.
* Update documentation appropriately.
* Made miscellaneous minor code style and optimization improvements within environments.
* Switched default Mac GFX API to Metal
* Added Barracuda pre-0.1.5
* Added basic integration with Barracuda Inference Engine
* Use predefined outputs the same way as for TF engine
* Fixed discrete action + LSTM support
* Switch Unity Mac Editor to Metal GFX API
* Fixed null model handling
* All examples converted to support Barracuda
* Added model conversion from Tensorflow to Barracuda
copied the barracuda.py file to ml-agents/mlagents/trainers
copied the tensorflow_to_barracuda.py file to ml-agents/mlagents/trainers
modified the tensorflow_to_barracuda.py file so it could be called from mlagents
modified ml-agents/mlagents/trainers/policy.py to convert the tf models to barracuda compatible .bytes file
* Added missing iOS BLAS plugin
* Added forgotten prefab changes
* Removed GLCore GFX backend for Mac, because it doesn't support Compute shaders
* Exposed GPU support for LearningBrain inference
...
* new env styles rebased on develop
* added new trained models
* renamed food collector platforms
* reduce training timescale on WallJump from 100 to 10
* uncheck academy control on walljump
* new banner image
* rename banner file
* new example env images
* add foodCollector image
* change Banana to FoodCollector and update image
* change bouncer description to include green cube
* update image
* update gridworld image
* cleanup prefab names and tags
* updated soccer env to reference purple agent instead of red
* remove unused mats
* rename files
* remove more unused tags
* update image
* change platform to agent cube
* update text. change platform to agents head
* cleanup
* cleaned up weird unused meta files
* add new wall jump nn files and rename a prefab
* walker change stacked states from 5 to 1
walker collects physics observations so stacked states are not need...
* Bumping version on the release (#3615)
* Update examples project to 2018.4.18f1 (#3618)
From 2018.4.14f1. An internal package dependency was updated as
a side effect.
* Remove dead components from the examples scenes (#3619) (#3624)
* Improve warnings and exception if using unsupported combo
* add meta file
* fix unit test
* enforce onnx conversion (expect tf2 CI to fail) (#3600)
* Update error message
* Updated the release branch docs (#3621)
* Updated the release branch docs
* Edited the README
* make sure top-level timer is closed before writing
* Remove space from Product Name for examples
In #2588 it was suggested that the space in the Product Name for
our example environments causes confusion when using a default build
because of the need to escape the space in the build filename.
This change removes the space from the Product Name in the project's
player settings.
* [bug-fix] Incr...