├── .gitignore ├── CODE_OF_CONDUCT.md ├── LICENSE ├── README.md ├── docs ├── Agents-Editor-Interface.md ├── Example-Environments.md ├── Getting-Started-with-Balance-Ball.md ├── Limitations-&-Common-Issues.md ├── Making-a-new-Unity-Environment.md ├── Organizing-the-Scene.md ├── Readme.md ├── Training-on-Amazon-Web-Service.md ├── Unity-Agents---Python-API.md ├── Unity-Agents-Overview.md ├── Using-TensorFlow-Sharp-in-Unity-(Experimental).md ├── best-practices-ppo.md ├── best-practices.md ├── broadcast.md ├── curriculum.md ├── installation.md └── monitor.md ├── images ├── academy.png ├── agent.png ├── agents_diagram.png ├── balance.png ├── banner.png ├── brain.png ├── broadcast.png ├── crawler.png ├── curriculum.png ├── curriculum_progress.png ├── gridworld.png ├── internal_brain.png ├── math.png ├── monitor.png ├── normalization.png ├── player_brain.png ├── push.png ├── reacher.png ├── scene-hierarchy.png ├── tennis.png ├── unity-logo-rgb.png ├── unity-wide.png └── wall.png ├── python ├── Basics.ipynb ├── PPO.ipynb ├── README.md ├── curricula │ ├── push.json │ ├── test.json │ └── wall.json ├── ppo.py ├── ppo │ ├── __init__.py │ ├── history.py │ ├── models.py │ └── trainer.py ├── requirements.txt ├── setup.py ├── test_unityagents.py └── unityagents │ ├── __init__.py │ ├── brain.py │ ├── curriculum.py │ ├── environment.py │ └── exception.py └── unity-environment ├── Assets ├── ML-Agents.meta └── ML-Agents │ ├── Editor.meta │ ├── Editor │ ├── BrainEditor.cs │ └── BrainEditor.cs.meta │ ├── Examples.meta │ ├── Examples │ ├── 3DBall.meta │ ├── 3DBall │ │ ├── Prefabs.meta │ │ ├── Prefabs │ │ │ ├── Game.prefab │ │ │ └── Game.prefab.meta │ │ ├── Scene.unity │ │ ├── Scene.unity.meta │ │ ├── Scripts.meta │ │ ├── Scripts │ │ │ ├── Ball3DAcademy.cs │ │ │ ├── Ball3DAcademy.cs.meta │ │ │ ├── Ball3DAgent.cs │ │ │ ├── Ball3DAgent.cs.meta │ │ │ ├── Ball3DDecision.cs │ │ │ └── Ball3DDecision.cs.meta │ │ ├── TFModels.meta │ │ └── TFModels │ │ │ ├── 3DBall.bytes │ │ │ └── 3DBall.bytes.meta │ ├── Area.meta │ ├── Area │ │ ├── Materials.meta │ │ ├── Materials │ │ │ ├── agent.mat │ │ │ ├── agent.mat.meta │ │ │ ├── block.mat │ │ │ ├── block.mat.meta │ │ │ ├── goal.mat │ │ │ ├── goal.mat.meta │ │ │ ├── wall.mat │ │ │ └── wall.mat.meta │ │ ├── Prefabs.meta │ │ ├── Prefabs │ │ │ ├── Agent.prefab │ │ │ ├── Agent.prefab.meta │ │ │ ├── Block.prefab │ │ │ ├── Block.prefab.meta │ │ │ ├── GoalHolder.prefab │ │ │ ├── GoalHolder.prefab.meta │ │ │ ├── PushArea.prefab │ │ │ ├── PushArea.prefab.meta │ │ │ ├── WallArea.prefab │ │ │ └── WallArea.prefab.meta │ │ ├── Push.unity │ │ ├── Push.unity.meta │ │ ├── Scripts.meta │ │ ├── Scripts │ │ │ ├── Area.cs │ │ │ ├── Area.cs.meta │ │ │ ├── AreaAgent.cs │ │ │ ├── AreaAgent.cs.meta │ │ │ ├── AreaDecision.cs │ │ │ ├── AreaDecision.cs.meta │ │ │ ├── GoalInteract.cs │ │ │ ├── GoalInteract.cs.meta │ │ │ ├── Push.meta │ │ │ ├── Push │ │ │ │ ├── PushAcademy.cs │ │ │ │ ├── PushAcademy.cs.meta │ │ │ │ ├── PushAgent.cs │ │ │ │ ├── PushAgent.cs.meta │ │ │ │ ├── PushArea.cs │ │ │ │ └── PushArea.cs.meta │ │ │ ├── Wall.meta │ │ │ └── Wall │ │ │ │ ├── WallAcademy.cs │ │ │ │ ├── WallAcademy.cs.meta │ │ │ │ ├── WallAgent.cs │ │ │ │ ├── WallAgent.cs.meta │ │ │ │ ├── WallArea.cs │ │ │ │ └── WallArea.cs.meta │ │ ├── TFModels.meta │ │ ├── TFModels │ │ │ ├── Push.bytes │ │ │ ├── Push.bytes.meta │ │ │ ├── Wall.bytes │ │ │ └── Wall.bytes.meta │ │ ├── Wall.unity │ │ └── Wall.unity.meta │ ├── Basic.meta │ ├── Basic │ │ ├── Materials.meta │ │ ├── Materials │ │ │ ├── agent.mat │ │ │ ├── agent.mat.meta │ │ │ ├── goal.mat │ │ │ └── goal.mat.meta │ │ ├── Scene.unity │ │ ├── Scene.unity.meta │ │ ├── Scripts.meta │ │ └── Scripts │ │ │ ├── BasicAcademy.cs │ │ │ ├── BasicAcademy.cs.meta │ │ │ ├── BasicAgent.cs │ │ │ ├── BasicAgent.cs.meta │ │ │ ├── BasicDecision.cs │ │ │ └── BasicDecision.cs.meta │ ├── Crawler.meta │ ├── Crawler │ │ ├── Crawler.unity │ │ ├── Crawler.unity.meta │ │ ├── Resources.meta │ │ ├── Resources │ │ │ ├── Checker.mat │ │ │ ├── Checker.mat.meta │ │ │ ├── Crawler.prefab │ │ │ └── Crawler.prefab.meta │ │ ├── Scripts.meta │ │ ├── Scripts │ │ │ ├── CameraFollow.cs │ │ │ ├── CameraFollow.cs.meta │ │ │ ├── CrawlerAcademy.cs │ │ │ ├── CrawlerAcademy.cs.meta │ │ │ ├── CrawlerAgentConfigurable.cs │ │ │ ├── CrawlerAgentConfigurable.cs.meta │ │ │ ├── CrawlerBodyContact.cs │ │ │ ├── CrawlerBodyContact.cs.meta │ │ │ ├── CrawlerLegContact.cs │ │ │ └── CrawlerLegContact.cs.meta │ │ ├── TFModels.meta │ │ └── TFModels │ │ │ ├── crawler.bytes │ │ │ └── crawler.bytes.meta │ ├── GridWorld.meta │ ├── GridWorld │ │ ├── GridWorld.unity │ │ ├── GridWorld.unity.meta │ │ ├── Resources.meta │ │ ├── Resources │ │ │ ├── agent.prefab │ │ │ ├── agent.prefab.meta │ │ │ ├── goal.prefab │ │ │ ├── goal.prefab.meta │ │ │ ├── pit.prefab │ │ │ └── pit.prefab.meta │ │ ├── Scripts.meta │ │ ├── Scripts │ │ │ ├── GridAcademy.cs │ │ │ ├── GridAcademy.cs.meta │ │ │ ├── GridAgent.cs │ │ │ └── GridAgent.cs.meta │ │ ├── TFModels.meta │ │ └── TFModels │ │ │ ├── GridWorld.bytes │ │ │ └── GridWorld.bytes.meta │ ├── Reacher.meta │ ├── Reacher │ │ ├── Materials.meta │ │ ├── Materials │ │ │ ├── Goal.mat │ │ │ ├── Goal.mat.meta │ │ │ ├── Goal_on.mat │ │ │ ├── Goal_on.mat.meta │ │ │ ├── Hand.mat │ │ │ ├── Hand.mat.meta │ │ │ ├── Materials.meta │ │ │ ├── Materials │ │ │ │ ├── checker 1.mat │ │ │ │ ├── checker 1.mat.meta │ │ │ │ ├── checker.mat │ │ │ │ └── checker.mat.meta │ │ │ ├── checker.jpg │ │ │ └── checker.jpg.meta │ │ ├── Prefabs.meta │ │ ├── Prefabs │ │ │ ├── Agent.prefab │ │ │ └── Agent.prefab.meta │ │ ├── Scene.unity │ │ ├── Scene.unity.meta │ │ ├── Scripts.meta │ │ ├── Scripts │ │ │ ├── FlyCamera.cs │ │ │ ├── FlyCamera.cs.meta │ │ │ ├── ReacherAcademy.cs │ │ │ ├── ReacherAcademy.cs.meta │ │ │ ├── ReacherAgent.cs │ │ │ ├── ReacherAgent.cs.meta │ │ │ ├── ReacherDecision.cs │ │ │ ├── ReacherDecision.cs.meta │ │ │ ├── ReacherGoal.cs │ │ │ └── ReacherGoal.cs.meta │ │ ├── TFModels.meta │ │ └── TFModels │ │ │ ├── Reacher.bytes │ │ │ └── Reacher.bytes.meta │ ├── Tennis.meta │ └── Tennis │ │ ├── Materials.meta │ │ ├── Materials │ │ ├── NetMat.mat │ │ ├── NetMat.mat.meta │ │ ├── ballMat.physicMaterial │ │ ├── ballMat.physicMaterial.meta │ │ ├── invisible.mat │ │ ├── invisible.mat.meta │ │ ├── racketMat.physicMaterial │ │ ├── racketMat.physicMaterial.meta │ │ ├── sand.mat │ │ └── sand.mat.meta │ │ ├── Prefabs.meta │ │ ├── Prefabs │ │ ├── TennisArea.prefab │ │ └── TennisArea.prefab.meta │ │ ├── Racket.meta │ │ ├── Racket │ │ ├── Materials.meta │ │ ├── Materials │ │ │ ├── None.mat │ │ │ └── None.mat.meta │ │ ├── Racket.mtl │ │ ├── Racket.mtl.meta │ │ ├── Racket.obj │ │ ├── Racket.obj.meta │ │ ├── RacketTex.png │ │ └── RacketTex.png.meta │ │ ├── Scripts.meta │ │ ├── Scripts │ │ ├── TennisAcademy.cs │ │ ├── TennisAcademy.cs.meta │ │ ├── TennisAgent.cs │ │ ├── TennisAgent.cs.meta │ │ ├── TennisArea.cs │ │ ├── TennisArea.cs.meta │ │ ├── hitWall.cs │ │ └── hitWall.cs.meta │ │ ├── TFModels.meta │ │ ├── TFModels │ │ ├── Tennis.bytes │ │ └── Tennis.bytes.meta │ │ ├── Tennis.unity │ │ └── Tennis.unity.meta │ ├── Materials.meta │ ├── Materials │ ├── MaterialsBall.meta │ ├── MaterialsBall │ │ ├── Materials.meta │ │ ├── Materials │ │ │ ├── logo 1.mat │ │ │ ├── logo 1.mat.meta │ │ │ ├── logo 2.mat │ │ │ ├── logo 2.mat.meta │ │ │ ├── logo.mat │ │ │ └── logo.mat.meta │ │ ├── Text.mat │ │ ├── Text.mat.meta │ │ ├── floor.jpg │ │ ├── floor.jpg.meta │ │ ├── floor.mat │ │ ├── floor.mat.meta │ │ ├── logo.png │ │ └── logo.png.meta │ ├── MaterialsGrid.meta │ ├── MaterialsGrid │ │ ├── Floor.mat │ │ ├── Floor.mat.meta │ │ ├── Wall.mat │ │ ├── Wall.mat.meta │ │ ├── agent_mat.mat │ │ ├── agent_mat.mat.meta │ │ ├── goal_mat.mat │ │ ├── goal_mat.mat.meta │ │ ├── pit_mat.mat │ │ └── pit_mat.mat.meta │ ├── MaterialsTennis.meta │ ├── MaterialsTennis │ │ ├── bounce.physicMaterial │ │ └── bounce.physicMaterial.meta │ ├── UIDefault.mat │ ├── UIDefault.mat.meta │ ├── ball.mat │ └── ball.mat.meta │ ├── Plugins.meta │ ├── Plugins │ ├── JSON.meta │ └── JSON │ │ ├── Newtonsoft.Json.dll │ │ └── Newtonsoft.Json.dll.meta │ ├── Scripts.meta │ ├── Scripts │ ├── Academy.cs │ ├── Academy.cs.meta │ ├── Agent.cs │ ├── Agent.cs.meta │ ├── Brain.cs │ ├── Brain.cs.meta │ ├── Communicator.cs │ ├── Communicator.cs.meta │ ├── CoreBrain.cs │ ├── CoreBrain.cs.meta │ ├── CoreBrainExternal.cs │ ├── CoreBrainExternal.cs.meta │ ├── CoreBrainHeuristic.cs │ ├── CoreBrainHeuristic.cs.meta │ ├── CoreBrainInternal.cs │ ├── CoreBrainInternal.cs.meta │ ├── CoreBrainPlayer.cs │ ├── CoreBrainPlayer.cs.meta │ ├── Decision.cs │ ├── Decision.cs.meta │ ├── ExternalCommunicator.cs │ ├── ExternalCommunicator.cs.meta │ ├── Monitor.cs │ ├── Monitor.cs.meta │ ├── UnityAgentsException.cs │ └── UnityAgentsException.cs.meta │ ├── Template.meta │ └── Template │ ├── Scene.unity │ ├── Scene.unity.meta │ ├── Scripts.meta │ └── Scripts │ ├── TemplateAcademy.cs │ ├── TemplateAcademy.cs.meta │ ├── TemplateAgent.cs │ ├── TemplateAgent.cs.meta │ ├── TemplateDecision.cs │ └── TemplateDecision.cs.meta ├── ProjectSettings ├── AudioManager.asset ├── ClusterInputManager.asset ├── DynamicsManager.asset ├── EditorBuildSettings.asset ├── EditorSettings.asset ├── GraphicsSettings.asset ├── InputManager.asset ├── NavMeshAreas.asset ├── NetworkManager.asset ├── Physics2DSettings.asset ├── ProjectSettings.asset ├── ProjectVersion.txt ├── QualitySettings.asset ├── TagManager.asset ├── TimeManager.asset └── UnityConnectSettings.asset └── README.md /.gitignore: -------------------------------------------------------------------------------- 1 | /unity-environment/[Ll]ibrary/ 2 | /unity-environment/[Tt]emp/ 3 | /unity-environment/[Oo]bj/ 4 | /unity-environment/[Bb]uild/ 5 | /unity-environment/[Bb]uilds/ 6 | /unity-environment/[Pp]ackages/ 7 | /unity-environment/[Uu]nity[Pp]ackage[Mm]anager/ 8 | /unity-environment/Assets/AssetStoreTools* 9 | 10 | # Tensorflow Model Info 11 | /python/models 12 | /python/summaries 13 | 14 | # Environemnt logfile 15 | *unity-environment.log 16 | 17 | # Visual Studio 2015 cache directory 18 | /unity-environment/.vs/ 19 | 20 | # Autogenerated VS/MD/Consulo solution and project files 21 | /unity-environmentExportedObj/ 22 | /unity-environment.consulo/ 23 | *.csproj 24 | *.unityproj 25 | *.sln 26 | *.suo 27 | *.tmp 28 | *.user 29 | *.userprefs 30 | *.pidb 31 | *.booproj 32 | *.svd 33 | *.pdb 34 | 35 | # Unity3D generated meta files 36 | *.pidb.meta 37 | 38 | # Unity3D Generated File On Crash Reports 39 | /unity-environment/sysinfo.txt 40 | 41 | # Builds 42 | *.apk 43 | *.unitypackage 44 | *.app 45 | *.exe 46 | *.x86_64 47 | *.x86 48 | 49 | # Tensorflow Sharp Files 50 | /unity-environment/Assets/ML-Agents/Plugins/Android* 51 | /unity-environment/Assets/ML-Agents/Plugins/iOS* 52 | /unity-environment/Assets/ML-Agents/Plugins/Computer* 53 | /unity-environment/Assets/ML-Agents/Plugins/System* 54 | 55 | 56 | # Mac hidden files 57 | *.DS_Store 58 | */.ipynb_checkpoints 59 | */.idea 60 | *.pyc 61 | *.idea/misc.xml 62 | *.idea/modules.xml 63 | *.iml 64 | *.xml 65 | *.cache 66 | */build/ 67 | */dist/ 68 | *.egg-info* 69 | *.eggs* 70 | *.gitignore.swp 71 | 72 | .DS_Store 73 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | 3 | # Unity ML - Agents (Beta) 4 | 5 | **Unity Machine Learning Agents** allows researchers and developers to 6 | create games and simulations using the Unity Editor which serve as 7 | environments where intelligent agents can be trained using 8 | reinforcement learning, neuroevolution, or other machine learning 9 | methods through a simple-to-use Python API. For more information, see 10 | the [documentation page](docs). 11 | 12 | For a walkthrough on how to train an agent in one of the provided 13 | example environments, start 14 | [here](docs/Getting-Started-with-Balance-Ball.md). 15 | 16 | ## Features 17 | * Unity Engine flexibility and simplicity 18 | * Multiple observations (cameras) 19 | * Flexible Multi-agent support 20 | * Discrete and continuous action spaces 21 | * Python (2 and 3) control interface 22 | * Visualizing network outputs in environment 23 | * Easily definable Curriculum Learning scenarios 24 | * Broadcasting of Agent behavior for supervised learning 25 | * Tensorflow Sharp Agent Embedding _[Experimental]_ 26 | 27 | ## Creating an Environment 28 | 29 | The _Agents SDK_, including example environment scenes is located in 30 | `unity-environment` folder. For requirements, instructions, and other 31 | information, see the contained Readme and the relevant 32 | [documentation](docs/Making-a-new-Unity-Environment.md). 33 | 34 | ## Training your Agents 35 | 36 | Once you've built a Unity Environment, example Reinforcement Learning 37 | algorithms and the Python API are available in the `python` 38 | folder. For requirements, instructions, and other information, see the 39 | contained Readme and the relevant 40 | [documentation](docs/Unity-Agents---Python-API.md). 41 | -------------------------------------------------------------------------------- /docs/Organizing-the-Scene.md: -------------------------------------------------------------------------------- 1 | # Organizing the Scene Layout 2 | 3 | This tutorial will help you understand how to organize your scene when using Agents in your Unity environment. 4 | 5 | ## ML-Agents Game Objects 6 | 7 | There are three kinds of game objects you need to include in your scene in order to use Unity ML-Agents: 8 | * Academy 9 | * Brain 10 | * Agents 11 | 12 | #### Keep in mind : 13 | * There can only be one Academy game object in a scene. 14 | * You can have multiple Brain game objects but they must be child of the Academy game object. 15 | 16 | #### Here is an example of what your scene hierarchy should look like : 17 | 18 | ![Scene Hierarchy](../images/scene-hierarchy.png) 19 | 20 | ### Functionality 21 | 22 | #### The Academy 23 | The Academy is responsible for: 24 | * Synchronizing the environment and keeping all agent's steps in pace. As such, there can only be one per scene. 25 | * Determining the speed of the engine, its quality, and the display's resolution. 26 | * Modifying the environment at every step and every reset according to the logic defined in `AcademyStep()` and `AcademyReset()`. 27 | * Coordinating the Brains which must be set as children of the Academy. 28 | 29 | #### Brains 30 | Each brain corresponds to a specific Decision-making method. This often aligns with a specific neural network model. The brain is responsible for deciding the action of all the Agents which are linked to it. There can be multiple brains in the same scene and multiple agents can subscribe to the same brain. 31 | 32 | #### Agents 33 | Each agent within a scene takes actions according to the decisions provided by it's linked Brain. There can be as many Agents of as many types as you like in the scene. The state size and action size of each agent must match the brain's parameters in order for the Brain to decide actions for it. 34 | -------------------------------------------------------------------------------- /docs/Readme.md: -------------------------------------------------------------------------------- 1 | # Unity ML Agents Documentation 2 | 3 | ## About 4 | * [Unity ML Agents Overview](Unity-Agents-Overview.md) 5 | * [Example Environments](Example-Environments.md) 6 | 7 | ## Tutorials 8 | * [Installation & Set-up](installation.md) 9 | * [Getting Started with the Balance Ball Environment](Getting-Started-with-Balance-Ball.md) 10 | * [Making a new Unity Environment](Making-a-new-Unity-Environment.md) 11 | * [How to use the Python API](Unity-Agents---Python-API.md) 12 | 13 | ## Features 14 | * [Agents SDK Inspector Descriptions](Agents-Editor-Interface.md) 15 | * [Scene Organization](Organizing-the-Scene.md) 16 | * [Curriculum Learning](curriculum.md) 17 | * [Broadcast](broadcast.md) 18 | * [Monitor](monitor.md) 19 | * [Training on the Cloud with Amazon Web Services](Training-on-Amazon-Web-Service.md) 20 | * [TensorflowSharp in Unity [Experimental]](Using-TensorFlow-Sharp-in-Unity-(Experimental).md) 21 | 22 | ## Best Practices 23 | * [Best practices when creating an Environment](best-practices.md) 24 | * [Best practices when training using PPO](best-practices-ppo.md) 25 | 26 | ## Help 27 | * [Limitations & Common Issues](Limitations-&-Common-Issues.md) 28 | -------------------------------------------------------------------------------- /docs/best-practices.md: -------------------------------------------------------------------------------- 1 | # Environment Design Best Practices 2 | 3 | ## General 4 | * It is often helpful to start with the simplest version of the problem, to ensure the agent can learn it. From there increase 5 | complexity over time. This can either be done manually, or via Curriculum Learning, where a set of lessons which progressively increase in difficulty are presented to the agent ([learn more here](../docs/curriculum.md)). 6 | * When possible, it is often helpful to ensure that you can complete the task by using a Player Brain to control the agent. 7 | 8 | ## Rewards 9 | * The magnitude of any given reward should typically not be greater than 1.0 in order to ensure a more stable learning process. 10 | * Positive rewards are often more helpful to shaping the desired behavior of an agent than negative rewards. 11 | * For locomotion tasks, a small positive reward (+0.1) for forward velocity is typically used. 12 | * If you want the agent to finish a task quickly, it is often helpful to provide a small penalty every step (-0.05) that the agent does not complete the task. In this case completion of the task should also coincide with the end of the episode. 13 | * Overly-large negative rewards can cause undesirable behavior where an agent learns to avoid any behavior which might produce the negative reward, even if it is also behavior which can eventually lead to a positive reward. 14 | 15 | ## States 16 | * States should include all variables relevant to allowing the agent to take the optimally informed decision. 17 | * Categorical state variables such as type of object (Sword, Shield, Bow) should be encoded in one-hot fashion (ie `3` -> `0, 0, 1`). 18 | * Besides encoding non-numeric values, all inputs should be normalized to be in the range 0 to +1 (or -1 to 1). For example rotation information on GameObjects should be recorded as `state.Add(transform.rotation.eulerAngles.y/180.0f-1.0f);` rather than `state.Add(transform.rotation.y);`. See the equation below for one approach of normaliztaion. 19 | * Positional information of relevant GameObjects should be encoded in relative coordinates wherever possible. This is often relative to the agent position. 20 | 21 | ![normalization](../images/normalization.png) 22 | 23 | ## Actions 24 | * When using continuous control, action values should be clipped to an appropriate range. 25 | * Be sure to set the action-space-size to the number of used actions, and not greater, as doing the latter can interfere with the efficency of the training process. 26 | -------------------------------------------------------------------------------- /docs/broadcast.md: -------------------------------------------------------------------------------- 1 | # Using the Broadcast Feature 2 | The Player, Heuristic and Internal brains have been updated to support broadcast. The broadcast feature allows you to collect data from your agents in python without controling them. 3 | ## How to use : Unity 4 | To turn it on in Unity, simply check the `Broadcast` box as shown bellow: 5 | 6 | ![Broadcast](../images/broadcast.png) 7 | 8 | ## How to use : Python 9 | When you launch your Unity Environment from python, you can see what the agents connected to non-external brains are doing. When calling `step` or `reset` on your environment, you retrieve a dictionary from brain names to `BrainInfo` objects. Each `BrainInfo` the non-external brains set to broadcast. 10 | Just like with an external brain, the `BrainInfo` object contains the fields for `observations`, `states`, `memories`,`rewards`, `local_done`, `agents` and `previous_actions`. Note that `previous_actions` corresponds to the actions that were taken by the agents at the previous step, not the current one. 11 | Note that when you do a `step` on the environment, you cannot provide actions for non-external brains. If there are no external brains in the scene, simply call `step()` with no arguments. 12 | You can use the broadcast feature to collect data generated by Player, Heuristics or Internal brains game sessions. You can then use this data to train an agent in a supervised context. 13 | -------------------------------------------------------------------------------- /docs/installation.md: -------------------------------------------------------------------------------- 1 | # Installation & Set-up 2 | 3 | ## Install **Unity 2017.1** or later (required) 4 | 5 | Download link available [here](https://store.unity.com/download?ref=update). 6 | 7 | ## Clone the repository 8 | Once installed, you will want to clone the Agents GitHub repository. References will be made 9 | throughout to `unity-environment` and `python` directories. Both are located at the root of the repository. 10 | 11 | ## Installing Python API 12 | In order to train an agent within the framework, you will need to install Python 2 or 3, and the dependencies described below. 13 | 14 | ### Windows Users 15 | 16 | If you are a Windows user who is new to Python/TensorFlow, follow [this guide](https://unity3d.college/2017/10/25/machine-learning-in-unity3d-setting-up-the-environment-tensorflow-for-agentml-on-windows-10/) to set up your Python environment. 17 | 18 | ### Requirements 19 | * Jupyter 20 | * Matplotlib 21 | * numpy 22 | * Pillow 23 | * Python (2 or 3; 64bit required) 24 | * docopt (Training) 25 | * TensorFlow (1.0+) (Training) 26 | 27 | ### Installing Dependencies 28 | To install dependencies, go into the `python` sub-directory of the repository, and run (depending on your python version) from the command line: 29 | 30 | `pip install .` 31 | 32 | or 33 | 34 | `pip3 install .` 35 | 36 | If your Python environment doesn't include `pip`, see these [instructions](https://packaging.python.org/guides/installing-using-linux-tools/#installing-pip-setuptools-wheel-with-linux-package-managers) on installing it. 37 | 38 | Once the requirements are successfully installed, the next step is to check out the [Getting Started guide](Getting-Started-with-Balance-Ball.md). 39 | 40 | ## Installation Help 41 | 42 | ### Using Jupyter Notebook 43 | 44 | For a walkthrough of how to use Jupyter notebook, see [here](http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/execute.html). 45 | 46 | ### General Issues 47 | 48 | If you run into issues while attempting to install and run Unity ML Agents, see [here](https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Limitations-&-Common-Issues.md) for a list of common issues and solutions. 49 | 50 | If you have an issue that isn't covered here, feel free to contact us at ml-agents@unity3d.com. Alternatively, feel free to create an issue on the repository. 51 | Be sure to include relevant information on OS, Python version, and exact error message if possible. 52 | -------------------------------------------------------------------------------- /docs/monitor.md: -------------------------------------------------------------------------------- 1 | # Using the Monitor 2 | 3 | ![Monitor](../images/monitor.png) 4 | 5 | The monitor allows visualizing information related to the agents or training process within a Unity scene. 6 | 7 | You can track many different things both related and unrelated to the agents themselves. To use the Monitor, call the Log function anywhere in your code : 8 | ```csharp 9 | Monitor.Log(key, value, displayType , target) 10 | ``` 11 | * *`key`* is the name of the information you want to display. 12 | * *`value`* is the information you want to display. 13 | * *`displayType`* is a MonitorType that can be either `text`, `slider`, `bar` or `hist`. 14 | * `text` will convert `value` into a string and display it. It can be useful for displaying error messages! 15 | * `slider` is used to display a single float between -1 and 1. Note that value must be a float if you want to use a slider. If the value is positive, the slider will be green, if the value is negative, the slider will be red. 16 | * `hist` is used to display multiple floats. Note that value must be a list or array of floats. The Histogram will be a sequence of vertical sliders. 17 | * `bar` is used to see the proportions. Note that value must be a list or array of positive floats. For each float in values, a rectangle of width of value divided by the sum of all values will be show. It is best for visualizing values that sum to 1. 18 | * *`target`* is the transform to which you want to attach information. 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https://raw.githubusercontent.com/c-barron/ml-agents/b43a41d93e03841a67a7c93d1ac4451155c63966/images/unity-wide.png -------------------------------------------------------------------------------- /images/wall.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/c-barron/ml-agents/b43a41d93e03841a67a7c93d1ac4451155c63966/images/wall.png -------------------------------------------------------------------------------- /python/README.md: -------------------------------------------------------------------------------- 1 | ![alt text](../images/banner.png "Unity ML - Agents") 2 | 3 | # Unity ML - Agents (Python API) 4 | 5 | ## Python Setup 6 | 7 | ### Requirements 8 | * Jupyter 9 | * docopt 10 | * Matplotlib 11 | * numpy 12 | * Pillow 13 | * Python (2 or 3) 14 | * Tensorflow (1.0+) 15 | 16 | ### Installing Dependencies 17 | To install dependencies, run: 18 | 19 | `pip install .` 20 | 21 | or 22 | 23 | `pip3 install .` 24 | 25 | If your Python environment doesn't include `pip`, see these [instructions](https://packaging.python.org/guides/installing-using-linux-tools/#installing-pip-setuptools-wheel-with-linux-package-managers) on installing it. 26 | 27 | ## Provided Jupyter Notebooks 28 | 29 | * **Basic** - Demonstrates usage of `UnityEnvironment` class for launching and interfacing with Unity Environments. 30 | * **PPO** - Used for training agents. Contains an implementation of Proximal Policy Optimization Reinforcement Learning algorithm. 31 | 32 | ### Running each notebook 33 | 34 | To launch jupyter, run: 35 | 36 | `jupyter notebook` 37 | 38 | Then navigate to `localhost:8888` to access each training notebook. 39 | 40 | To monitor training progress, run the following from the root directory of this repo: 41 | 42 | `tensorboard --logdir=summaries` 43 | 44 | Then navigate to `localhost:6006` to monitor progress with Tensorboard. 45 | 46 | ## Training PPO directly 47 | 48 | To train using PPO without the notebook, run: `python3 ppo.py --train` 49 | 50 | Where `` corresponds to the name of the built Unity environment. 51 | 52 | For a list of additional hyperparameters, run: `python3 ppo.py --help` 53 | 54 | ## Using Python API 55 | See this [documentation](../docs/Unity-Agents---Python-API.md) for a detailed description of the functions and uses of the Python API. 56 | 57 | ## Training on AWS 58 | See this related [blog post](https://medium.com/towards-data-science/how-to-run-unity-on-amazon-cloud-or-without-monitor-3c10ce022639) for a description of how to run Unity Environments on AWS EC2 instances with the GPU. 59 | -------------------------------------------------------------------------------- /python/curricula/push.json: -------------------------------------------------------------------------------- 1 | { 2 | "measure" : "reward", 3 | "thresholds" : [0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75], 4 | "min_lesson_length" : 2, 5 | "signal_smoothing" : true, 6 | "parameters" : 7 | { 8 | "goal_size" : [3.5, 3.25, 3.0, 2.75, 2.5, 2.25, 2.0, 1.75, 1.5, 1.25, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 9 | "block_size": [1.5, 1.4, 1.3, 1.2, 1.1, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 10 | "x_variation":[1.5, 1.55, 1.6, 1.65, 1.7, 1.75, 1.8, 1.85, 1.9, 1.95, 2.0, 2.1, 2.2, 2.3, 2.4, 2.5] 11 | } 12 | } 13 | -------------------------------------------------------------------------------- /python/curricula/test.json: -------------------------------------------------------------------------------- 1 | { 2 | "measure" : "reward", 3 | "thresholds" : [10, 20, 50], 4 | "min_lesson_length" : 3, 5 | "signal_smoothing" : true, 6 | "parameters" : 7 | { 8 | "param1" : [0.7, 0.5, 0.3, 0.1], 9 | "param2" : [100, 50, 20, 15], 10 | "param3" : [0.2, 0.3, 0.7, 0.9] 11 | } 12 | } 13 | -------------------------------------------------------------------------------- /python/curricula/wall.json: -------------------------------------------------------------------------------- 1 | { 2 | "measure" : "reward", 3 | "thresholds" : [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], 4 | "min_lesson_length" : 2, 5 | "signal_smoothing" : true, 6 | "parameters" : 7 | { 8 | "min_wall_height" : [0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5], 9 | "max_wall_height" : [1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0] 10 | } 11 | } 12 | -------------------------------------------------------------------------------- /python/ppo/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/c-barron/ml-agents/b43a41d93e03841a67a7c93d1ac4451155c63966/python/ppo/__init__.py -------------------------------------------------------------------------------- /python/requirements.txt: -------------------------------------------------------------------------------- 1 | tensorflow>=1.0 2 | Pillow>=4.2.1 3 | matplotlib 4 | numpy>=1.11.0 5 | jupyter 6 | mock>=2.0.0 7 | pytest>=3.2.2 8 | docopt -------------------------------------------------------------------------------- /python/setup.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | from setuptools import setup, Command, find_packages 4 | 5 | 6 | with open('requirements.txt') as f: 7 | required = f.read().splitlines() 8 | 9 | setup(name='unityagents', 10 | version='0.2.0', 11 | description='Unity Machine Learning Agents', 12 | license='Apache License 2.0', 13 | author='Unity Technologies', 14 | author_email='ML-Agents@unity3d.com', 15 | url='https://github.com/Unity-Technologies/ml-agents', 16 | packages=find_packages(exclude = ['ppo']), 17 | install_requires = required, 18 | long_description= ("Unity Machine Learning Agents allows researchers and developers " 19 | "to transform games and simulations created using the Unity Editor into environments " 20 | "where intelligent agents can be trained using reinforcement learning, evolutionary " 21 | "strategies, or other machine learning methods through a simple to use Python API.") 22 | ) 23 | -------------------------------------------------------------------------------- /python/unityagents/__init__.py: -------------------------------------------------------------------------------- 1 | from .environment import * 2 | from .brain import * 3 | from .exception import * 4 | from .curriculum import * 5 | -------------------------------------------------------------------------------- /python/unityagents/brain.py: -------------------------------------------------------------------------------- 1 | class BrainInfo: 2 | def __init__(self, observation, state, memory=None, reward=None, agents=None, local_done=None, action =None): 3 | """ 4 | Describes experience at current step of all agents linked to a brain. 5 | """ 6 | self.observations = observation 7 | self.states = state 8 | self.memories = memory 9 | self.rewards = reward 10 | self.local_done = local_done 11 | self.agents = agents 12 | self.previous_actions = action 13 | 14 | 15 | class BrainParameters: 16 | def __init__(self, brain_name, brain_param): 17 | """ 18 | Contains all brain-specific parameters. 19 | :param brain_name: Name of brain. 20 | :param brain_param: Dictionary of brain parameters. 21 | """ 22 | self.brain_name = brain_name 23 | self.state_space_size = brain_param["stateSize"] 24 | self.number_observations = len(brain_param["cameraResolutions"]) 25 | self.camera_resolutions = brain_param["cameraResolutions"] 26 | self.action_space_size = brain_param["actionSize"] 27 | self.memory_space_size = brain_param["memorySize"] 28 | self.action_descriptions = brain_param["actionDescriptions"] 29 | self.action_space_type = ["discrete", "continuous"][brain_param["actionSpaceType"]] 30 | self.state_space_type = ["discrete", "continuous"][brain_param["stateSpaceType"]] 31 | 32 | def __str__(self): 33 | return '''Unity brain name: {0} 34 | Number of observations (per agent): {1} 35 | State space type: {2} 36 | State space size (per agent): {3} 37 | Action space type: {4} 38 | Action space size (per agent): {5} 39 | Memory space size (per agent): {6} 40 | Action descriptions: {7}'''.format(self.brain_name, 41 | str(self.number_observations), self.state_space_type, 42 | str(self.state_space_size), self.action_space_type, 43 | str(self.action_space_size), 44 | str(self.memory_space_size), 45 | ', '.join(self.action_descriptions)) 46 | -------------------------------------------------------------------------------- /python/unityagents/exception.py: -------------------------------------------------------------------------------- 1 | import logging 2 | logger = logging.getLogger("unityagents") 3 | 4 | class UnityEnvironmentException(Exception): 5 | """ 6 | Related to errors starting and closing environment. 7 | """ 8 | pass 9 | 10 | 11 | class UnityActionException(Exception): 12 | """ 13 | Related to errors with sending actions. 14 | """ 15 | pass 16 | 17 | class UnityTimeOutException(Exception): 18 | """ 19 | Related to errors with communication timeouts. 20 | """ 21 | def __init__(self, message, log_file_path = None): 22 | if log_file_path is not None: 23 | try: 24 | with open(log_file_path, "r") as f: 25 | printing = False 26 | unity_error = '\n' 27 | for l in f: 28 | l=l.strip() 29 | if (l == 'Exception') or (l=='Error'): 30 | printing = True 31 | unity_error += '----------------------\n' 32 | if (l == ''): 33 | printing = False 34 | if printing: 35 | unity_error += l + '\n' 36 | logger.info(unity_error) 37 | logger.error("An error might have occured in the environment. " 38 | "You can check the logfile for more information at {}".format(log_file_path)) 39 | except: 40 | logger.error("An error might have occured in the environment. " 41 | "No unity-environment.log file could be found.") 42 | super(UnityTimeOutException, self).__init__(message) 43 | 44 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 11630fa83cc8b4194b94352e3e6cdb9d 3 | folderAsset: yes 4 | timeCreated: 1504127524 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Editor.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 67b4fb0b937cc471eae742addf6bda86 3 | folderAsset: yes 4 | timeCreated: 1503177274 5 | licenseType: Free 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Editor/BrainEditor.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | using UnityEditor; 6 | using System.Linq; 7 | /* 8 | This code is meant to modify the behavior of the inspector on Brain Components. 9 | Depending on the type of brain that is used, the available fields will be modified in the inspector accordingly. 10 | */ 11 | [CustomEditor (typeof(Brain))] 12 | public class BrainEditor : Editor 13 | { 14 | public override void OnInspectorGUI () 15 | { 16 | Brain myBrain = (Brain)target; 17 | SerializedObject serializedBrain = serializedObject; 18 | 19 | if (myBrain.transform.parent == null) { 20 | EditorGUILayout.HelpBox ("A Brain GameObject must be a child of an Academy GameObject!", MessageType.Error); 21 | } else if (myBrain.transform.parent.GetComponent () == null) { 22 | EditorGUILayout.HelpBox ("The Parent of a Brain must have an Academy Component attached to it!", MessageType.Error); 23 | } 24 | 25 | BrainParameters parameters = myBrain.brainParameters; 26 | if (parameters.actionDescriptions == null || parameters.actionDescriptions.Length != parameters.actionSize) 27 | parameters.actionDescriptions = new string[parameters.actionSize]; 28 | 29 | serializedBrain.Update(); 30 | 31 | SerializedProperty bp = serializedBrain.FindProperty ("brainParameters"); 32 | EditorGUILayout.PropertyField(bp, true); 33 | 34 | SerializedProperty bt = serializedBrain.FindProperty("brainType"); 35 | EditorGUILayout.PropertyField(bt); 36 | 37 | if (bt.enumValueIndex < 0) { 38 | bt.enumValueIndex = (int)BrainType.Player; 39 | } 40 | 41 | serializedBrain.ApplyModifiedProperties(); 42 | 43 | myBrain.UpdateCoreBrains (); 44 | myBrain.coreBrain.OnInspector (); 45 | 46 | #if !NET_4_6 && ENABLE_TENSORFLOW 47 | EditorGUILayout.HelpBox ("You cannot have ENABLE_TENSORFLOW without NET_4_6", MessageType.Error); 48 | #endif 49 | } 50 | } 51 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Editor/BrainEditor.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: f1895a43ed0f54ffd9ee06234c4399e7 3 | timeCreated: 1503270350 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 6584f096f53dc43eeb32803b91f36c5c 3 | folderAsset: yes 4 | timeCreated: 1504127503 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: f8097eaa1623c4a8ab4eff559e20fedb 3 | folderAsset: yes 4 | timeCreated: 1504127718 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Prefabs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 7f76e451b3030e54eac0f7c5488d22e9 3 | folderAsset: yes 4 | timeCreated: 1506066534 5 | licenseType: Free 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Prefabs/Game.prefab.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: ff026d63a00abdc48ad6ddcff89aba04 3 | timeCreated: 1506066551 4 | licenseType: Free 5 | NativeFormatImporter: 6 | mainObjectFileID: 100100000 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Scene.unity.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: a83e830ec5bcd4b1db836428921d59b0 3 | timeCreated: 1497054080 4 | licenseType: Pro 5 | DefaultImporter: 6 | userData: 7 | assetBundleName: 8 | assetBundleVariant: 9 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Scripts.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 1aca8883d579a491ca2a55ea7a8127c3 3 | folderAsset: yes 4 | timeCreated: 1503455136 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DAcademy.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class Ball3DAcademy : Academy 6 | { 7 | public override void AcademyReset() 8 | { 9 | 10 | } 11 | 12 | public override void AcademyStep() 13 | { 14 | 15 | } 16 | } 17 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DAcademy.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: eb15e3c3d55e54abaafb74c635b6a458 3 | timeCreated: 1502223572 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DAgent.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: aaba48bf82bee4751aa7b89569e57f73 3 | timeCreated: 1502223572 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DDecision.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class Ball3DDecision : MonoBehaviour, Decision 6 | { 7 | public float[] Decide(List state, List observation, float reward, bool done, float[] memory) 8 | { 9 | if (gameObject.GetComponent().brainParameters.actionSpaceType == StateType.continuous) 10 | { 11 | List ret = new List(); 12 | if (state[2] < 0 || state[5] < 0) 13 | { 14 | ret.Add(state[5]); 15 | } 16 | else 17 | { 18 | ret.Add(state[5]); 19 | } 20 | if (state[3] < 0 || state[7] < 0) 21 | { 22 | ret.Add(-state[7]); 23 | } 24 | else 25 | { 26 | ret.Add(-state[7]); 27 | } 28 | return ret.ToArray(); 29 | 30 | } 31 | else 32 | { 33 | return new float[1]{ 1f }; 34 | } 35 | } 36 | 37 | public float[] MakeMemory(List state, List observation, float reward, bool done, float[] memory) 38 | { 39 | return new float[0]; 40 | } 41 | } 42 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DDecision.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: ccaa8f43c15264209b137d8dc26a8d63 3 | timeCreated: 1503595709 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/3DBall/TFModels.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 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assetBundleName: 8 | assetBundleVariant: 9 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: dd0ac6aeac49a4adcb3e8db0f7280fc0 3 | folderAsset: yes 4 | timeCreated: 1506303336 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Materials.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 8f94ab12d7c27400a998ea33e8163b40 3 | folderAsset: yes 4 | timeCreated: 1506189694 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | 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-------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Push.unity.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 1faf90b0c489d45aab7a6111f56bfc56 3 | timeCreated: 1506808980 4 | licenseType: Pro 5 | DefaultImporter: 6 | userData: 7 | assetBundleName: 8 | assetBundleVariant: 9 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: b412b865c66f042ad8cf9b2e2ae8ebad 3 | folderAsset: yes 4 | timeCreated: 1503355437 5 | licenseType: Free 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Area.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class Area : MonoBehaviour { 6 | 7 | // Use this for initialization 8 | void Start () { 9 | 10 | } 11 | 12 | // Update is called once per frame 13 | void Update () { 14 | 15 | } 16 | 17 | public virtual void ResetArea() { 18 | 19 | } 20 | } 21 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Area.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: b46b66a9b32b24fab9d7ffcca24f1f43 3 | timeCreated: 1506809357 4 | licenseType: Pro 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/AreaAgent.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: d1ed6eb5b71e34a75b416c45c4c6f39c 3 | timeCreated: 1506829089 4 | licenseType: Pro 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/AreaDecision.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class AreaDecision : MonoBehaviour, Decision { 6 | 7 | public float[] Decide (List state, List observation, float reward, bool done, float[] memory) 8 | { 9 | float[] action = new float[1]; 10 | action[0] = Random.Range(0, 5); 11 | return action; 12 | 13 | } 14 | 15 | public float[] MakeMemory (List state, List observation, float reward, bool done, float[] memory) 16 | { 17 | return default(float[]); 18 | 19 | } 20 | } 21 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/AreaDecision.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: c0205d4e23c794363ba1d78b1e3d7339 3 | timeCreated: 1503355437 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/GoalInteract.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class GoalInteract : MonoBehaviour 6 | { 7 | public GameObject myAgent; 8 | public GameObject myObject; 9 | // Use this for initialization 10 | void Start() 11 | { 12 | 13 | } 14 | 15 | // Update is called once per frame 16 | void Update() 17 | { 18 | 19 | } 20 | 21 | private void OnCollisionEnter(Collision collision) 22 | { 23 | if (collision.gameObject == myObject) 24 | { 25 | Agent agent = myAgent.GetComponent(); 26 | agent.done = true; 27 | agent.reward = 1f; 28 | } 29 | } 30 | 31 | } -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/GoalInteract.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 7f7d39fa1cc584f83aa99151c78122f4 3 | timeCreated: 1506304463 4 | licenseType: Pro 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: b807758e46f074b679b7e3ccadfc82c2 3 | folderAsset: yes 4 | timeCreated: 1507918266 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push/PushAcademy.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class PushAcademy : Academy { 6 | 7 | public float goalSize; 8 | public float blockSize; 9 | public float xVariation; 10 | 11 | public override void AcademyReset() 12 | { 13 | goalSize = (float)resetParameters["goal_size"]; 14 | blockSize = (float)resetParameters["block_size"]; 15 | xVariation = (float)resetParameters["x_variation"]; 16 | } 17 | 18 | public override void AcademyStep() 19 | { 20 | 21 | } 22 | 23 | } 24 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push/PushAcademy.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 0d8678972c7c0497584073f29b210d8d 3 | timeCreated: 1506829765 4 | licenseType: Pro 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push/PushAgent.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 49f021cd5b5ee49a7bbce654270e260e 3 | timeCreated: 1506829537 4 | licenseType: Pro 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push/PushArea.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class PushArea : Area { 6 | 7 | public GameObject block; 8 | public GameObject goalHolder; 9 | public GameObject academy; 10 | 11 | // Use this for initialization 12 | void Start () { 13 | academy = GameObject.Find("Academy"); 14 | } 15 | 16 | // Update is called once per frame 17 | void Update () { 18 | 19 | } 20 | 21 | public override void ResetArea() 22 | { 23 | float goalSize = academy.GetComponent().goalSize; 24 | float blockSize = academy.GetComponent().blockSize; 25 | float xVariation = academy.GetComponent().xVariation; 26 | 27 | block.transform.position = new Vector3(Random.Range(-xVariation, xVariation), 1f, -6f) + gameObject.transform.position; 28 | goalHolder.transform.position = new Vector3(Random.Range(-xVariation, xVariation), -0.1f, -2f) + gameObject.transform.position; 29 | goalSize = Random.Range(goalSize * 0.9f, goalSize * 1.1f); 30 | blockSize = Random.Range(blockSize * 0.9f, blockSize * 1.1f); 31 | block.transform.localScale = new Vector3(blockSize, 1f, blockSize); 32 | goalHolder.transform.localScale = new Vector3(goalSize, 1f, goalSize); 33 | } 34 | 35 | } 36 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push/PushArea.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 0572958da97104432a0f155301472bbb 3 | timeCreated: 1506809696 4 | licenseType: Pro 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 96f0da72d86b14ac293d14ce775e4dd4 3 | folderAsset: yes 4 | timeCreated: 1507918296 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallAcademy.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class WallAcademy : Academy { 6 | 7 | public float minWallHeight; 8 | public float maxWallHeight; 9 | 10 | public override void AcademyReset() 11 | { 12 | minWallHeight = (float)resetParameters["min_wall_height"]; 13 | maxWallHeight = (float)resetParameters["max_wall_height"]; 14 | } 15 | 16 | public override void AcademyStep() 17 | { 18 | 19 | } 20 | 21 | } 22 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallAcademy.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 3d90d7400713f423b9862a2ee7262eb7 3 | timeCreated: 1503355437 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallAgent.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class WallAgent : AreaAgent 6 | { 7 | public GameObject goalHolder; 8 | public GameObject block; 9 | public GameObject wall; 10 | 11 | public override void InitializeAgent() 12 | { 13 | base.InitializeAgent(); 14 | } 15 | 16 | public override List CollectState() 17 | { 18 | List state = new List(); 19 | Vector3 velocity = GetComponent().velocity; 20 | state.Add((transform.position.x - area.transform.position.x)); 21 | state.Add((transform.position.y - area.transform.position.y)); 22 | state.Add((transform.position.z + 5 - area.transform.position.z)); 23 | 24 | state.Add((goalHolder.transform.position.x - area.transform.position.x)); 25 | state.Add((goalHolder.transform.position.y - area.transform.position.y)); 26 | state.Add((goalHolder.transform.position.z + 5 - area.transform.position.z)); 27 | 28 | state.Add((block.transform.position.x - area.transform.position.x)); 29 | state.Add((block.transform.position.y - area.transform.position.y)); 30 | state.Add((block.transform.position.z + 5 - area.transform.position.z)); 31 | 32 | state.Add(wall.transform.localScale.y); 33 | 34 | state.Add(velocity.x); 35 | state.Add(velocity.y); 36 | state.Add(velocity.z); 37 | 38 | Vector3 blockVelocity = block.GetComponent().velocity; 39 | state.Add(blockVelocity.x); 40 | state.Add(blockVelocity.y); 41 | state.Add(blockVelocity.z); 42 | 43 | return state; 44 | } 45 | 46 | public override void AgentStep(float[] act) 47 | { 48 | reward = -0.005f; 49 | MoveAgent(act); 50 | 51 | if (gameObject.transform.position.y < 0.0f || 52 | Mathf.Abs(gameObject.transform.position.x - area.transform.position.x) > 8f || 53 | Mathf.Abs(gameObject.transform.position.z + 5 - area.transform.position.z) > 8) 54 | { 55 | done = true; 56 | reward = -1f; 57 | } 58 | } 59 | 60 | public override void AgentReset() 61 | { 62 | transform.position = new Vector3(Random.Range(-3.5f, 3.5f), 1.1f, -8f) + area.transform.position; 63 | GetComponent().velocity = new Vector3(0f, 0f, 0f); 64 | 65 | area.GetComponent().ResetArea(); 66 | } 67 | 68 | public override void AgentOnDone() 69 | { 70 | 71 | } 72 | } 73 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallAgent.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 4276057469b484664b731803aa947656 3 | timeCreated: 1503355437 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallArea.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class WallArea : Area { 6 | 7 | public GameObject wall; 8 | public GameObject academy; 9 | public GameObject block; 10 | public GameObject goalHolder; 11 | 12 | // Use this for initialization 13 | void Start () { 14 | academy = GameObject.Find("Academy"); 15 | } 16 | 17 | // Update is called once per frame 18 | void Update () { 19 | 20 | } 21 | 22 | public override void ResetArea() { 23 | float wallHeightMin = academy.GetComponent().minWallHeight; 24 | float wallHeightMax = academy.GetComponent().maxWallHeight; 25 | wall.transform.localScale = new Vector3(12f, Random.Range(wallHeightMin, wallHeightMax) - 0.1f, 1f); 26 | block.transform.position = new Vector3(Random.Range(-3.5f, 3.5f), 1f, Random.Range(-4f, -8f)) + gameObject.transform.position; 27 | goalHolder.transform.position = new Vector3(Random.Range(-3.5f, 3.5f), -0.1f, 0f) + gameObject.transform.position; 28 | } 29 | } 30 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallArea.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 8852782dcebdd427799bf307c5ef2314 3 | timeCreated: 1506809294 4 | licenseType: Pro 5 | MonoImporter: 6 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/unity-environment/Assets/ML-Agents/Examples/Basic/Materials/goal.mat.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 624b24bbec31f44babfb57ef2dfbc537 3 | timeCreated: 1506189863 4 | licenseType: Pro 5 | NativeFormatImporter: 6 | mainObjectFileID: 2100000 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Basic/Scene.unity.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: cf1d119a8748d406e90ecb623b45f92f 3 | timeCreated: 1504127824 4 | licenseType: Pro 5 | DefaultImporter: 6 | userData: 7 | assetBundleName: 8 | assetBundleVariant: 9 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Basic/Scripts.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: fbcbd038eb29041f580c463e454e10fc 3 | folderAsset: yes 4 | timeCreated: 1503355437 5 | licenseType: Free 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Basic/Scripts/BasicAcademy.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class BasicAcademy : Academy { 6 | 7 | public override void AcademyReset() 8 | { 9 | 10 | } 11 | 12 | public override void AcademyStep() 13 | { 14 | 15 | } 16 | 17 | } 18 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Basic/Scripts/BasicAcademy.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 19276d4dc78ee49f1ba258293f17636c 3 | timeCreated: 1503355437 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Basic/Scripts/BasicAgent.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class BasicAgent : Agent 6 | { 7 | 8 | public int position; 9 | public int smallGoalPosition; 10 | public int largeGoalPosition; 11 | public GameObject largeGoal; 12 | public GameObject smallGoal; 13 | public int minPosition; 14 | public int maxPosition; 15 | 16 | public override List CollectState() 17 | { 18 | List state = new List(); 19 | state.Add(position); 20 | return state; 21 | } 22 | 23 | public override void AgentStep(float[] act) 24 | { 25 | float movement = act[0]; 26 | int direction = 0; 27 | if (movement == 0) { direction = -1; } 28 | if (movement == 1) { direction = 1; } 29 | 30 | position += direction; 31 | if (position < minPosition) { position = minPosition; } 32 | if (position > maxPosition) { position = maxPosition; } 33 | 34 | gameObject.transform.position = new Vector3(position, 0f, 0f); 35 | 36 | reward -= 0.01f; 37 | 38 | if (position == smallGoalPosition) 39 | { 40 | done = true; 41 | reward = 0.1f; 42 | } 43 | 44 | if (position == largeGoalPosition) 45 | { 46 | done = true; 47 | reward = 1f; 48 | } 49 | } 50 | 51 | public override void AgentReset() 52 | { 53 | position = 0; 54 | minPosition = -10; 55 | maxPosition = 10; 56 | smallGoalPosition = -3; 57 | largeGoalPosition = 7; 58 | smallGoal.transform.position = new Vector3(smallGoalPosition, 0f, 0f); 59 | largeGoal.transform.position = new Vector3(largeGoalPosition, 0f, 0f); 60 | } 61 | 62 | public override void AgentOnDone() 63 | { 64 | 65 | } 66 | } 67 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Basic/Scripts/BasicAgent.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 624480a72e46148118ab2e2d89b537de 3 | timeCreated: 1503355437 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Basic/Scripts/BasicDecision.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class BasicDecision : MonoBehaviour, Decision 6 | { 7 | 8 | public float[] Decide(List state, List observation, float reward, bool done, float[] memory) 9 | { 10 | return new float[1]{ 1f }; 11 | 12 | } 13 | 14 | public float[] MakeMemory(List state, List observation, float reward, bool done, float[] memory) 15 | { 16 | return new float[0]; 17 | 18 | } 19 | } 20 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Basic/Scripts/BasicDecision.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 99399d2439f894b149d8e67b85b6e07a 3 | timeCreated: 1503355437 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 0efc731e39fd04495bee94884abad038 3 | folderAsset: yes 4 | timeCreated: 1509574928 5 | licenseType: Free 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Crawler.unity.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 4cf841b0478fb4b33971627b40c6420b 3 | timeCreated: 1508521562 4 | licenseType: Free 5 | DefaultImporter: 6 | userData: 7 | assetBundleName: 8 | assetBundleVariant: 9 | -------------------------------------------------------------------------------- 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m_Texture: {fileID: 0} 51 | m_Scale: {x: 1, y: 1} 52 | m_Offset: {x: 0, y: 0} 53 | - _ParallaxMap: 54 | m_Texture: {fileID: 0} 55 | m_Scale: {x: 1, y: 1} 56 | m_Offset: {x: 0, y: 0} 57 | m_Floats: 58 | - _BumpScale: 1 59 | - _Cutoff: 0.5 60 | - _DetailNormalMapScale: 1 61 | - _DstBlend: 0 62 | - _GlossMapScale: 1 63 | - _Glossiness: 0.5 64 | - _GlossyReflections: 1 65 | - _Metallic: 0 66 | - _Mode: 0 67 | - _OcclusionStrength: 1 68 | - _Parallax: 0.02 69 | - _SmoothnessTextureChannel: 0 70 | - _SpecularHighlights: 1 71 | - _SrcBlend: 1 72 | - _UVSec: 0 73 | - _ZWrite: 1 74 | m_Colors: 75 | - _Color: {r: 1, g: 1, b: 1, a: 1} 76 | - _EmissionColor: {r: 0, g: 0, b: 0, a: 1} 77 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Resources/Checker.mat.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 53c99f11939b0417eacfe91c06beadfb 3 | timeCreated: 1508523154 4 | licenseType: Free 5 | NativeFormatImporter: 6 | mainObjectFileID: 2100000 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Resources/Crawler.prefab.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 3db4283e33af74336bfedb01d0e011bf 3 | timeCreated: 1508548205 4 | licenseType: Free 5 | NativeFormatImporter: 6 | mainObjectFileID: 100100000 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 464b7b589acd8464c8c447efa71f95ed 3 | folderAsset: yes 4 | timeCreated: 1508478093 5 | licenseType: Free 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CameraFollow.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class CameraFollow : MonoBehaviour { 6 | 7 | public Transform target; 8 | Vector3 offset; 9 | 10 | // Use this for initialization 11 | void Start () { 12 | offset = gameObject.transform.position - target.position; 13 | } 14 | 15 | // Update is called once per frame 16 | void Update () { 17 | //gameObject.transform.position = target.position + offset; 18 | Vector3 newPosition = new Vector3(target.position.x + offset.x, transform.position.y, target.position.z + offset.z); 19 | gameObject.transform.position = newPosition; 20 | } 21 | } 22 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CameraFollow.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: ec40c70d5160b47cd8deaab79e24892c 3 | timeCreated: 1508523647 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerAcademy.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class CrawlerAcademy : Academy 6 | { 7 | public override void InitializeAcademy() 8 | { 9 | Monitor.verticalOffset = 1f; 10 | } 11 | 12 | public override void AcademyReset() 13 | { 14 | 15 | 16 | } 17 | 18 | public override void AcademyStep() 19 | { 20 | 21 | 22 | } 23 | } 24 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerAcademy.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 19a3d2012efe74376a579f7f8fbfe13d 3 | timeCreated: 1507584900 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerAgentConfigurable.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: aeeb12a8f17db49f095fd1936d2798c9 3 | timeCreated: 1507411991 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerBodyContact.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class CrawlerBodyContact : MonoBehaviour { 6 | 7 | CrawlerAgentConfigurable agent; 8 | 9 | void Start(){ 10 | agent = gameObject.transform.parent.gameObject.GetComponent(); 11 | } 12 | 13 | void OnTriggerEnter(Collider other){ 14 | if (other.gameObject.name == "Ground") 15 | { 16 | agent.fell = true; 17 | } 18 | } 19 | } 20 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerBodyContact.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: a1c672528369d465e9d8cd7511a7f679 3 | timeCreated: 1507592528 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerLegContact.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class CrawlerLegContact : MonoBehaviour { 6 | 7 | public int index; 8 | public CrawlerAgentConfigurable agent; 9 | 10 | void Start(){ 11 | // agent = gameObject.transform.parent.gameObject.GetComponent(); 12 | } 13 | 14 | void OnCollisionStay(Collision other){ 15 | if (other.gameObject.name == "Platform") 16 | { 17 | agent.leg_touching[index] = true; 18 | } 19 | } 20 | 21 | } 22 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerLegContact.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 2b1c61949ba3445eea83275fb5ce32c5 3 | timeCreated: 1507591712 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherAcademy.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class ReacherAcademy : Academy { 6 | 7 | public float goalSize; 8 | public float goalSpeed; 9 | 10 | 11 | public override void AcademyReset() 12 | { 13 | goalSize = (float)resetParameters["goal_size"]; 14 | goalSpeed = (float)resetParameters["goal_speed"]; 15 | } 16 | 17 | public override void AcademyStep() 18 | { 19 | 20 | 21 | } 22 | 23 | } 24 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherAcademy.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 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-------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class ReacherDecision : MonoBehaviour, Decision { 6 | 7 | public float[] Decide (List state, List observation, float reward, bool done, float[] memory) 8 | { 9 | float[] action = new float[4]; 10 | for (int i = 0; i < 4; i++) { 11 | action[i] = Random.Range(-1f, 1f); 12 | } 13 | return action; 14 | 15 | } 16 | 17 | public float[] MakeMemory (List state, List observation, float reward, bool done, float[] memory) 18 | { 19 | return default(float[]); 20 | 21 | } 22 | } 23 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherDecision.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: ab9b9df01a69049778c72ce49b13cfd9 3 | timeCreated: 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-------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 1ccbe12ca56a942148cb40eb57d25d1f 3 | folderAsset: yes 4 | timeCreated: 1502511502 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Tennis/Scripts/TennisAcademy.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | using UnityEngine.UI; 5 | 6 | public class TennisAcademy : Academy 7 | { 8 | 9 | public override void AcademyReset() 10 | { 11 | } 12 | 13 | public override void AcademyStep() 14 | { 15 | } 16 | 17 | } 18 | -------------------------------------------------------------------------------- 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assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Examples/Tennis/Scripts/TennisArea.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class TennisArea : MonoBehaviour { 6 | 7 | public GameObject ball; 8 | public GameObject agentA; 9 | public GameObject agentB; 10 | 11 | // Use this for initialization 12 | void Start () { 13 | 14 | } 15 | 16 | // Update is called once per frame 17 | void Update () { 18 | 19 | } 20 | 21 | public void MatchReset() { 22 | float ballOut = Random.Range(4f, 11f); 23 | int flip = Random.Range(0, 2); 24 | if (flip == 0) 25 | { 26 | ball.transform.position = new Vector3(-ballOut, 5f, 0f) + transform.position; 27 | } 28 | else 29 | { 30 | ball.transform.position = new Vector3(ballOut, 5f, 0f) + transform.position; 31 | } 32 | 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assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/Agent.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 88b6042bc9a5d4aa58d931eae49442e5 3 | timeCreated: 1501802662 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/Brain.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: c676a8ddf5a5f4f64b35e9ed5028679d 3 | timeCreated: 1503211687 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/Communicator.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | /** \brief AcademyParameters is a structure containing basic information about the 6 | * training environment. */ 7 | /** The AcademyParameters will be sent via socket at the start of the Environment. 8 | * This structure does not need to be modified. 9 | */ 10 | public struct AcademyParameters 11 | { 12 | public string AcademyName; 13 | /**< \brief The name of the Academy. If the communicator is External, 14 | * it will be the name of the Academy GameObject */ 15 | public string apiNumber; 16 | /**< \brief The API number for the communicator. */ 17 | public string logPath; 18 | /**< \brief The location of the logfile*/ 19 | public Dictionary resetParameters; 20 | /**< \brief The default reset parameters are sent via socket*/ 21 | public List brainNames; 22 | /**< \brief A list of the all the brains names sent via socket*/ 23 | public List brainParameters; 24 | /**< \brief A list of the External brains parameters sent via socket*/ 25 | public List externalBrainNames; 26 | /**< \brief A list of the External brains names sent via socket*/ 27 | } 28 | 29 | public enum ExternalCommand 30 | { 31 | STEP, 32 | RESET, 33 | QUIT 34 | } 35 | 36 | /** 37 | * This is the interface used to generate coordinators. 38 | * This does not need to be modified nor implemented to create a 39 | * Unity environment. 40 | */ 41 | public interface Communicator 42 | { 43 | 44 | /// Implement this method to allow brains to subscribe to the 45 | /// decisions made outside of Unity 46 | void SubscribeBrain(Brain brain); 47 | 48 | /// First contact between Communicator and external process 49 | bool CommunicatorHandShake(); 50 | 51 | /// Implement this method to initialize the communicator 52 | void InitializeCommunicator(); 53 | 54 | /// Implement this method to receive actions from outside of Unity and 55 | /// update the actions of the brains that subscribe 56 | void UpdateActions(); 57 | 58 | /// Implement this method to return the ExternalCommand that 59 | /// was given outside of Unity 60 | ExternalCommand GetCommand(); 61 | 62 | /// Implement this method to return the new dictionary of resetParameters 63 | /// that was given outside of Unity 64 | Dictionary GetResetParameters(); 65 | 66 | 67 | } 68 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/Communicator.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 18600657fd7d241a199e6caf2ba7cceb 3 | timeCreated: 1504820023 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/CoreBrain.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | /** \brief An interface which defines the functions needed for a CoreBrain. */ 6 | /** There is no need to modify or implement CoreBrain to create a Unity environment. 7 | */ 8 | public interface CoreBrain 9 | { 10 | 11 | /// Implement setBrain so let the coreBrain know what brain is using it 12 | void SetBrain(Brain b); 13 | /// Implement this method to initialize CoreBrain 14 | void InitializeCoreBrain(); 15 | /// Implement this method to define the logic for deciding actions 16 | void DecideAction(); 17 | /// Implement this method to define the logic for sending the actions 18 | void SendState(); 19 | /// Implement this method to define what should be displayed in the brain Inspector 20 | void OnInspector(); 21 | 22 | } 23 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/CoreBrain.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: dcbf9c1714a8d4b819ce2caa23b2eaf4 3 | timeCreated: 1504070234 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/CoreBrainExternal.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | /// CoreBrain which decides actions via communication with an external system such as Python. 6 | public class CoreBrainExternal : ScriptableObject, CoreBrain 7 | { 8 | 9 | public Brain brain; 10 | /**< Reference to the brain that uses this CoreBrainExternal */ 11 | 12 | ExternalCommunicator coord; 13 | 14 | /// Creates the reference to the brain 15 | public void SetBrain(Brain b) 16 | { 17 | brain = b; 18 | } 19 | 20 | /// Generates the communicator for the Academy if none was present and 21 | /// subscribe to ExternalCommunicator if it was present. 22 | public void InitializeCoreBrain() 23 | { 24 | if (brain.gameObject.transform.parent.gameObject.GetComponent().communicator == null) 25 | { 26 | coord = null; 27 | throw new UnityAgentsException(string.Format("The brain {0} was set to" + 28 | " External mode" + 29 | " but Unity was unable to read the" + 30 | " arguments passed at launch.", brain.gameObject.name)); 31 | } 32 | else if (brain.gameObject.transform.parent.gameObject.GetComponent().communicator is ExternalCommunicator) 33 | { 34 | coord = (ExternalCommunicator)brain.gameObject.transform.parent.gameObject.GetComponent().communicator; 35 | coord.SubscribeBrain(brain); 36 | } 37 | 38 | } 39 | 40 | /// Uses the communicator to retrieve the actions, memories and values and 41 | /// sends them to the agents 42 | public void DecideAction() 43 | { 44 | if (coord != null) 45 | { 46 | brain.SendActions(coord.GetDecidedAction(brain.gameObject.name)); 47 | brain.SendMemories(coord.GetMemories(brain.gameObject.name)); 48 | brain.SendValues(coord.GetValues(brain.gameObject.name)); 49 | } 50 | } 51 | 52 | /// Uses the communicator to send the states, observations, rewards and 53 | /// dones outside of Unity 54 | public void SendState() 55 | { 56 | if (coord != null) 57 | { 58 | coord.giveBrainInfo(brain); 59 | } 60 | } 61 | 62 | /// Nothing needs to appear in the inspector 63 | public void OnInspector() 64 | { 65 | 66 | } 67 | } 68 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/CoreBrainExternal.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 35813a1be64e144f887d7d5f15b963fa 3 | timeCreated: 1504070319 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/CoreBrainHeuristic.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 943466ab374444748a364f9d6c3e2fe2 3 | timeCreated: 1504070366 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/CoreBrainInternal.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 8b23992c8eb17439887f5e944bf04a40 3 | timeCreated: 1504070347 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/CoreBrainPlayer.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 41e9bda8f3cf1492fa74926a530f6f70 3 | timeCreated: 1504070375 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/Decision.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | /// Generic functions for Decision Interface 6 | public interface Decision 7 | { 8 | /// \brief Implement this method to define the logic of decision making 9 | /// for the CoreBrainHeuristic 10 | /** Given the information about the agent, return a vector of actions. 11 | * @param state The state of the agent 12 | * @param observation The cameras the agent uses 13 | * @param reward The reward the agent had at the previous step 14 | * @param done Weather or not the agent is done 15 | * @param memory The memories stored from the previous step with MakeMemory() 16 | * @return The vector of actions the agent will take at the next step 17 | */ 18 | float[] Decide(List state, List observation, float reward, bool done, float[] memory); 19 | 20 | /// \brief Implement this method to define the logic of memory making for 21 | /// the CoreBrainHeuristic 22 | /** Given the information about the agent, return the new memory vector for the agent. 23 | * @param state The state of the agent 24 | * @param observation The cameras the agent uses 25 | * @param reward The reward the agent had at the previous step 26 | * @param done Weather or not the agent is done 27 | * @param memory The memories stored from the previous step with MakeMemory() 28 | * @return The vector of memories the agent will use at the next step 29 | */ 30 | float[] MakeMemory(List state, List observation, float reward, bool done, float[] memory); 31 | } -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/Decision.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 13e74744309fd4571b76e46fafc6d37f 3 | timeCreated: 1503182472 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/ExternalCommunicator.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 9685de855ca1541409f4187c5ab7601d 3 | timeCreated: 1504820023 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/Monitor.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: e59a31a1cc2f5464d9a61bef0bc9a53b 3 | timeCreated: 1508031727 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/UnityAgentsException.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | using System; 6 | [System.Serializable] 7 | /// Contains exceptions specific to ML-Agents. 8 | public class UnityAgentsException : System.Exception 9 | { 10 | /// When a UnityAgentsException is called, the timeScale is set to 0. 11 | /// The simulation will end since no steps will be taken. 12 | public UnityAgentsException(string message) : base(message) 13 | { 14 | Time.timeScale = 0f; 15 | } 16 | 17 | /// A constructor is needed for serialization when an exception propagates 18 | /// from a remoting server to the client. 19 | protected UnityAgentsException(System.Runtime.Serialization.SerializationInfo info, 20 | System.Runtime.Serialization.StreamingContext context) 21 | { } 22 | } 23 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Scripts/UnityAgentsException.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: e63e4a66d820245778f9a2abfa5b68e0 3 | timeCreated: 1504131359 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Template.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 11b74a3b21c094e088c0e9fb4d4167ee 3 | folderAsset: yes 4 | timeCreated: 1504127695 5 | licenseType: Pro 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Template/Scene.unity.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: e81622878c805493fb0e3d0e0141e7c6 3 | timeCreated: 1504127824 4 | licenseType: Pro 5 | DefaultImporter: 6 | userData: 7 | assetBundleName: 8 | assetBundleVariant: 9 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Template/Scripts.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 7180b2e9f97774db6a291c04dceba7ca 3 | folderAsset: yes 4 | timeCreated: 1503355437 5 | licenseType: Free 6 | DefaultImporter: 7 | userData: 8 | assetBundleName: 9 | assetBundleVariant: 10 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Template/Scripts/TemplateAcademy.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class TemplateAcademy : Academy { 6 | 7 | public override void AcademyReset() 8 | { 9 | 10 | 11 | } 12 | 13 | public override void AcademyStep() 14 | { 15 | 16 | 17 | } 18 | 19 | } 20 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Template/Scripts/TemplateAcademy.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 9af83cd96d4bc4088a966af174446d1b 3 | timeCreated: 1503355437 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Template/Scripts/TemplateAgent.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class TemplateAgent : Agent { 6 | 7 | 8 | 9 | public override List CollectState() 10 | { 11 | List state = new List(); 12 | 13 | return state; 14 | } 15 | 16 | public override void AgentStep(float[] act) 17 | { 18 | 19 | } 20 | 21 | public override void AgentReset() 22 | { 23 | 24 | } 25 | 26 | public override void AgentOnDone() 27 | { 28 | 29 | } 30 | } 31 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Template/Scripts/TemplateAgent.cs.meta: -------------------------------------------------------------------------------- 1 | fileFormatVersion: 2 2 | guid: 33bb739f1138d40798114d667776a1d6 3 | timeCreated: 1503355437 4 | licenseType: Free 5 | MonoImporter: 6 | serializedVersion: 2 7 | defaultReferences: [] 8 | executionOrder: 0 9 | icon: {instanceID: 0} 10 | userData: 11 | assetBundleName: 12 | assetBundleVariant: 13 | -------------------------------------------------------------------------------- /unity-environment/Assets/ML-Agents/Template/Scripts/TemplateDecision.cs: -------------------------------------------------------------------------------- 1 | using System.Collections; 2 | using System.Collections.Generic; 3 | using UnityEngine; 4 | 5 | public class TemplateDecision : MonoBehaviour, Decision 6 | { 7 | 8 | public float[] Decide(List state, List observation, float reward, bool done, float[] memory) 9 | { 10 | return new float[0]; 11 | 12 | } 13 | 14 | public float[] MakeMemory(List state, List observation, float reward, bool done, float[] memory) 15 | { 16 | return new float[0]; 17 | 18 | } 19 | } 20 | 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