* [Semantics] Modified the semantics for the documentation
* [Semantics] Updated the images
* [Semantics] Made further changes to the docs based of the comments received
- Mostly ensures consistency with our other guides, in addition to including some more detail.
- Added an image to showcase the Linux Build Support for Unity.
- Updated the Installation guide to reference the Linux Build Support component.
* [Documentation] Added the On Demand Decision documentation.
* [Fixes] Corrected grammar mistakes
* [Documentation] Adding what kinds of games ODD is useful for
* [Documentation] Added the LSTM documentation
* [Documentation] Fix the line breaks
* [Documentations] Modified the doc given feedback
* [Documentation] Improvements based of PR comments
* [Documentation] Removed reference to PPO and BC
* [New Bouncer] Revamped the Bouncer to be in 3D
* [Bouncer Configuration file] Added the BouncerBrain configuration
* [Documentation] Added the Bouncer tot he documentation page
* [Fixes] Fixed lines too long and the documentation typo
* Slight adjustments to bouncer environment
* Don't default to internal brain on bouncer
- Cleaned up text
- Renamed file
- Updated ML-Agents-Overview to point to new file
- Updated figure to showcase the new “On Demand Decisions” checkbox text
* [Documentation] Added description on how to add visual observations
* [Documentation] Forgot a paragraph
* [Documentation] Addressed comments
* [Documentation] Addressed comments, again
* Minor changes to ensure a common visual language.
* Agents are blue (or additionally red in competitive scenarios).
* Interactable objects are orange.
* Goals are green when objects, and checkerboards when places.
* Not everything perfectly follows this, but things are mostly consistent now.
* Renamed "Banana" folder to "BananaCollectors"
* Ensured all brains were set to "Player"
* Moved non-shared assets out of the "SharedAssets" folder.
* some random change so that I can create this PR
* docs update for TensorFlowSharp new version
* changed the links to the new unitypackage file
* resolved conflicts, updated the pictures for CUDA 9.0
* fixed a typo
* resolved arthur's comment
* blurred the usernames
* modified the AWS doc
* resolved Vince's comment
* Adds implementation of Curiosity-driven Exploration by Self-supervised Prediction (https://arxiv.org/abs/1705.05363) to PPO trainer.
* To enable, set use_curiosity flag to true in hyperparameter file.
* Includes refactor of unitytrainers model code to accommodate new feature.
* Adds new Pyramids environment (w/ documentation). Environment contains sparse reward, and can only be solved using PPO+Curiosity.
* Revamps agent code for walker and crawler environments to use shared JointDriveController system.
* Crawler has been reworked to be very cute.
* Crawler & Walker environments have been reworked to be visually consistent.
* Added Dynamic Crawler scene.
* All scenes re-trained and new models added.
* Documentation changes.
* Initial Commit
Ported most functionalities, still need to :
- Documentation
- Add Comments
- Custom drawer for BrainParameters
- Fix the UnitTests
- Review Functionalities
* Added Custom Drawer for the Brain Parameters
* Improvements to the HubDrawer
* Modified the Brain Editors
* Minor bug fixes and UI changes
* Modified the Help Boxes of the Drawers
* Modified Brain class, renamed Initialize and made DecideAction virtual
* Fix the UnityTests
* Simpler Brain creation menu
* Renamed Internal Brain to Learning Brain
* modified the parameters to remove reference to External or Internal in the Protobuf objects
* Updated the protobuf generated files
* Fix the Pytests
* Removed the graph scope from the Learning Brain
* cleaner logic than try catch
* Removed the isExternal field of the brain and put the isTraining logic into LearningBrain and Training Hub
* Modified how the Brain finds the A...
* Fix Typo #1323
* First update to the docs
* Addressed comments
* remove references to TF#
* Replaced the references to TF# with new document.
* Edditied the FAQ
* Documentation Update
* addressed comments
* new images for the recorder
* Improvements to the docs
* Address the comments
* Core_ML typo
* Updated the links to inference repo
* Put back Inference-Engine.md
* fix typos : brain
* Readd deleted file
* fix typos
* Addressed comments
* Simplified rewards and observations; Determined better settings for training within a reasonable amount of time.
* Simplified Agent rewards; Added training section that discusses hyperparameters.
* Added note about DecisionFrequency.
* Updated screenshots and a small clarification in the text.
* Tested and updated using v0.6.
* Update a couple of images, minor text edit.
* Replace with more recent training stats.
* resolve a couple of minor review commnts.
* Increased the recommended batch and buffer size hyperparameter values.
* Fix 2 typos.
* Wording and filepath changes to tutorials
* Retake editor images to match v0.6
Retake editor images so that the filepaths and Brain names match what they actually are.
* 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
...
* Added RenderTexture support for visual observations
* Cleaned up new ObservationToTexture function
* Added check for to width/height of RenderTexture
* Added check to hide HelpBox unless both cameras and RenderTextures are used
* Added documentation for Visual Observations using RenderTextures
* Added GridWorldRenderTexture Example scene
* Adjusted image size of doc images
* Added GridWorld example reference
* Fixed missing reference in the GridWorldRenderTexture scene and resaved the agent prefab
* Fix prefab instantiation and render timing in GridWorldRenderTexture
* Added screenshot and reworded documentation
* Unchecked control box
* Rename renderTexture
* Make RenderTexture scene default for GridWorld
Co-authored-by: Mads Johansen <pyjamads@gmail.com>
Based on the new reward signals architecture, add BC pretrainer and GAIL for PPO. Main changes:
- A new GAILRewardSignal and GAILModel for GAIL/VAIL
- A BCModule component (not a reward signal) to do pretraining during RL
- Documentation for both of these
- Change to Demo Loader that lets you load multiple demo files in a folder
- Example Demo files for all of our tested sample environments (for future regression testing)
* Add Sampler and SamplerManager
* Enable resampling of reset parameters during training
* Documentation for Sampler and example YAML configuration file
* 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...
* Feature Deprecation : Online Behavioral Cloning
In this PR :
- Delete the online_bc_trainer
- Delete the tests for online bc
- delete the configuration file for online bc training
* Deleting the BCTeacherHelper.cs Script
TODO :
- Remove usages in the scene
- Documentation Edits
*DO NOT MERGE*
* IMPORTANT : REMOVED ALL IL SCENES
- Removed all the IL scenes from the Examples folder
* Removed all mentions of online BC training in the Documentation
* Made a note in the Migrating.md doc about the removal of the Online BC feature.
* Modified the Academy UI to remove the control checkbox and replaced it with a train in the editor checkbox
* Removed the Broadcast functionality from the non-Learning brains
* Bug fix
* Note that the scenes are broken since the BroadcastHub has changed
* Modified the LL-API for Python to remove the broadcasting functiuonality.
* All unit tests are running
* Modified the scen...
* 1 to 1 Brain to Agent
This is a work in progess
In this PR :
- Deleted all Brain Objects
- Moved the BrainParameters into the Agent
- Gave the Agent a Heuristic method (see Balance Ball for example)
- Modified the Communicator and ModelRunner : Put can only take one agent at a time
- Made the IBrain Interface with RequestDecision and DecideAction method
No changes made to Python
[Design Doc](https://docs.google.com/document/d/1hBhBxZ9lepGF4H6fc6Hu6AW7UwOmnyX3trmgI3HpOmo/edit#)
* Removing editorconfig
* Updating BallanceBall scene
* grammar mistake
* Clearing the Agents of the Model runner
* Added Documentation on IBrain
* Modified comments on GiveModel
* Introduced a factory
* Split Learning Brain in two
* Changes to walljump
* Fixing the Unit tests
* Renaming the Brain to Policy
* Heuristic now has priority over training
* Edited code comments
* Fixing bugs
* Develop one to one scene edits...
* [WIP] Side Channel initial layout
* Working prototype for raw bytes
* fixing format mistake
* Added some errors and some unit tests in C#
* Added the side channel for the Engine Configuration. (#2958)
* Added the side channel for the Engine Configuration.
Note that this change does not require modifying a lot of files :
- Adding a sender in Python
- Adding a receiver in C#
- subscribe the receiver to the communicator (here is a one liner in the Academy)
- Add the side channel to the Python UnityEnvironment (not represented here)
Adding the side channel to the environment would look like such :
```python
from mlagents.envs.environment import UnityEnvironment
from mlagents.envs.side_channel.raw_bytes_channel import RawBytesChannel
from mlagents.envs.side_channel.engine_configuration_channel import EngineConfigurationChannel
channel0 = RawBytesChannel()
channel1 = EngineConfigurationChanne...
Convert the UnitySDK to a Packman Package.
- Separate Examples into a sample project.
- Move core UnitySDK Code into com.unity.ml-agents.
- Create asmdefs for the ml-agents package.
- Add package validation tests for win/linux/max.
- Update protobuf generation scripts.
- Add Barracuda as a package dependency for ML-Agents. (users no longer have to install it themselves).
* Improvements to the main repo Readme: put an emphasis on the Releases section.
* Improving the installation guide.
* Added the first draft of package readme.
* Removed the unused images from the images folder. Used the command
```
for f in *; do echo " file : $f" && grep -s -r "$f" /Users/vincentpierre/Documents/ml-agents -i --include *.md --exclude-dir=/Users/vincentpierre/Documents/ml-agents/docs/localized;done
```
to hunt the files down
* Modified the Unity Editor screenshots
* Addressing comments
* Improvements to Learning-Environment-Create-New.md
- Changed the ordered list to use "1."
- Trimmed down text
- Removed reference to materials as those are in the Example Envs project
* Incorporated PR feedback + new images.
* factor in feedback
removed unnecessary configs
updated the agent image
* Formatting fix
* Improvements to Key Components section of ML-Agents Overview
- Moved some documentation from Learning-Environment-Design.
- Added the trainers vs LL-API separation.
- Made a note about gym-unity.
- Some update to the Agent/Behavior sections
- Updated diagrams to reflect new side channels. Made Behavior type a consistent color.
* Reorganizing the overview file and creating new (empty) sections
This change defines the new structure for the overview doc. Subsequent commits will fill in the sections and rewrite existing sections.
* Reorganizing the main Training ML-Agents page
Re-organizes into feature-specific sections that somewhat mirror the previous commit of reorganizing the overview doc.
Subsequent commits will populate these empty sections.
* Adding Deep RL
- Update ML-Agents-Overview with description of DeepRL training algorithms
- Decribe the common and trainer-specific hyperparams in Training-ML-Agents.
- Removed ...
* about to implement orientation cube
* oCube spawining works. ready to train
* working. about to try com
* ready for training
* add random rot on episode start
* feet now alternate but runs backwards
* still running with right leg in front
* increased joint strength to 40k
* removed texture example
* reduced maxAngVel, enabled enhanced determinism, cont spec
* rebuilt walker ragdoll to scale 1
* rebuilt ragdoll ready
* update walker pair prefab
* fixed bp heirarchy
* added trained model, renamed scene, usecollisioncallbacks
* updated dynamic platforms
* added dynamic walker tf file. max speed 5
* DynamicWalker working. has working nn file
* collect local rotations
* added new dynamic nn file
* hip facing reward
* Create WalkerDynamic.yaml
* fix hip rotation
* about to clean up code
* added dirIndicator and orentCubeGizmo
* clean up
* clea...
* about to implement orientation cube
* oCube spawining works. ready to train
* working. about to try com
* ready for training
* add random rot on episode start
* feet now alternate but runs backwards
* still running with right leg in front
* increased joint strength to 40k
* removed texture example
* reduced maxAngVel, enabled enhanced determinism, cont spec
* rebuilt walker ragdoll to scale 1
* rebuilt ragdoll ready
* update walker pair prefab
* fixed bp heirarchy
* added trained model, renamed scene, usecollisioncallbacks
* updated dynamic platforms
* added dynamic walker tf file. max speed 5
* DynamicWalker working. has working nn file
* collect local rotations
* added new dynamic nn file
* hip facing reward
* Create WalkerDynamic.yaml
* fix hip rotation
* about to clean up code
* added dirIndicator and orentCubeGizmo
* clean up
* cleanup
* up...
* updated image in learning envs examples
* add link to learning example to match-3
* cleaned up headings
* removed anchor
* Update Match3.md
* Delete match3.png
* added new match3 image
* updated match3 image link
* Removing some scenes, All the Static and all the non variable speed environments. Also removed Bouncer, PushBlock, WallJump and reacher. Removed a bunch of visual environements as well. Removed 3DBallHard and FoodCollector (kept Visual and Grid FoodCollector)
* readding 3DBallHard
* readding pushblock and walljump
* Removing tennis
* removing mentions of removed environments
* removing unused images
* Renaming Crawler demos
* renaming some demo files
* removing and modifying some config files
* new examples image?
* removing Bouncer from build list
* replacing the Bouncer environment with Match3 for llapi tests
* Typo in yamato test
* Aded the Goal conditioned GridWorld to replace regular gridworld
* adding missing files
* Code improvements
* Documentation change on gridworld
* resolving conflicts
* new model
* Addressing comments
* comments and renames
* Update docs/Learning-Environment-Examples.md
Co-authored-by: Ervin T. <ervin@unity3d.com>
* adding reference to gridworld in docs about goal signal
Co-authored-by: Chris Elion <chris.elion@unity3d.com>
Co-authored-by: Ervin T. <ervin@unity3d.com>
Arthur Juliani
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