RayPerception moved to a component that is now used by Banana, Soccer, Hallway, and Push Block.
Converted Push Block to use RayPerception for local perception and retrained model.
Re-worked Hallway to be more extensible.
* 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...
* 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...
* Triming some of the methods of the agent but left SetReward
* Fixing bugs
* modifying the environments
* Reintroducing IsDone and IsMaxStepReached
* Updating the Migrating doc
* more details on the Migration
Initial commit
second commit. The no-extrinsic was trained without the log reward (reward = prob) while the new one is (reward = log_prob - log_prior)
A few results, it looks like Walker-diverse-r05-bigger.onnx is doing something
Modified pushblock
using next state and action. Did not help
Fixing bug that had 9 diversity settings instead of 8
removing results
GitHub
Vincent(Yuan) Gao
Vincent-Pierre BERGES
Ervin T
Jonathan Harper
Yuan Gao
vincentpierre