* [Semantics] Modified the semantics for the documentation
* [Semantics] Updated the images
* [Semantics] Made further changes to the docs based of the comments received
* 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.
* 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
* Create new class (RewardSignal) that represents a reward signal.
* Add value heads for each reward signal in the PPO model.
* Make summaries agnostic to the type of reward signals, and log weighted rewards per reward signal.
* Move extrinsic and curiosity rewards into this new structure.
* Allow defining multiple reward signals in YAML file. Add documentation for this new structure.
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)
* Included explicit version # for ZN
* added explicit version for KR docs
* minor fix in installation doc
* Consistency with numbers for reset parameters
* Removed extra verbiage. minor consistency
* minor consistency
* Cleaned up IL language
* moved parameter sampling above in list
* Cleaned up language in Env Parameter sampling
* Cleaned up migrating content
* updated consistency of Reset Parameter Sampling
* Rename Training-Generalization-Learning.md to Training-Generalization-Reinforcement-Learning-Agents.md
* Updated doc link for generalization
* Rename Training-Generalization-Reinforcement-Learning-Agents.md to Training-Generalized-Reinforcement-Learning-Agents.md
* Re-wrote the intro paragraph for generalization
* add titles, cleaned up language for reset params
* Update Training-Generalized-Reinforcement-Learning-Agents.md
* cleanup of generalization doc
* More cleanu...
* Add Soft Actor-Critic model, trainer, and policy and sac_trainer_config.yaml
* Add documentation for SAC and tweak PPO documentation to reference the new pages.
* Add tests for SAC, change simple_rl test to run both PPO and SAC.
* 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...
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).
* Merge agent & best practices doc. Plus other fixes
* Fix overly long lines
* Merge Getting Started and Basic Guides
* Rename guide and update links appropriately
* Fix broken link
Merged the "Overview" sections of a few pages into their respective sections in ML-Agents-Overview:
- Training-Using-Concurrent-Unity-Instances.md
- Training-Self-Play.md
- Training-SAC.md
- Training-PPO.md
- Training-Imitation-Learning.md
- Training-Environment-Parameter-Randomization.md
- Training-Curriculum-Learning.md
- Reward-Signals.md
- Feature-Monitor.md
- Feature-Memory.md
Organized ML-Agents-Overview into Training Methods and Training Options sections.
Follow-up action items (part of a separate PR):
- Smooth over the documentation in ML-Agents-Overview (right now, we somewhat just pasted text from other pages). If we align on the new structure for this page, we can iterate on it.
- Update “Key Components” section with new graph and discuss side channels and revise use of Academy.
- Consolidate “Training-*” docs into Training-ML-Agents to offer a single guide for all hyperparameter selection
Arthur Juliani
GitHub
eshvk
Joe Ward
Marwan Mattar
vincentpierre
Deric Pang
Jeffrey Shih
Yuan Gao
Ervin Teng