Unity
From Robin
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== Notes on deterministic behavior == | == Notes on deterministic behavior == | ||
- | To ensure determinism, it seems that the physics of a scene needs to be reset. This can be done by loading a scene whenever you are evaluating something. Note that when coupling Python and Unity in the ''Editor Mode'', experiments will not be deterministic. You will have to build and run an executable of your project to get deterministic behavior. | + | To ensure determinism, it seems that the physics of a scene needs to be reset. This can be done by loading a scene whenever you are evaluating something. Note that when coupling Python and Unity in the ''Editor Mode'', experiments will not be deterministic. You will have to build and run an executable of your project to get deterministic behavior. One can subscribe a function to the ''Academy.Instance.OnEnvironmentReset'' event in Unity that loads the scene containing the robot. |
[[Unity-Timing-David | David's tips on getting deterministic timing]] | [[Unity-Timing-David | David's tips on getting deterministic timing]] |
Revision as of 09:15, 1 November 2022
Contents |
Installation
Download and install Unity
Installing Unity ML-Agents
In the Unity editor, go to window->package manager. Inside the package manager search for ML agents in the Unity Registry. Install the most recent ML Agents package. ML-Agents examples can be downloaded from the ML-Agents Github
Setting up the Python API
pip install mlagents
Using Unity ML-Agents
Running ML-Agents through the Python API
You can interact with Unity ML-Agents by [1] opening Unity through python (env = UnityEnvironment(side_channels=[])), [2] resetting the environment (env.reset()), [3] stepping the environment forward until a new input from python is required (env.step()), [4] getting the state of the agent (with any sensory information; env.get_steps(behavior_name: str)) and [5] setting the actions for agents (env.set_actions(behavior_name: str, action: ActionTuple)). For more information, please consult the guides below.
Documentation
Unity ML-Agents Github Page Unity Documentation
Troubleshooting
Although it is in principle quite easy to set up a Unity ML-Agents environment, in practice there can be a few tricky bugs either with Unity failing to start, version incompatibilities, or dependencies. If you're having specific issues with Unity and/or ML-Agents, for now, contact Frank.
Getting rid of too many log messages in the terminal
Depending on your experiments, it can be the case that you'll see that Unity is sending a bit too many messages. To limit the number of log messages, go to Project Settings->Player->Other Settings->Stack Trace and adjust the settings accordingly.
Notes on deterministic behavior
To ensure determinism, it seems that the physics of a scene needs to be reset. This can be done by loading a scene whenever you are evaluating something. Note that when coupling Python and Unity in the Editor Mode, experiments will not be deterministic. You will have to build and run an executable of your project to get deterministic behavior. One can subscribe a function to the Academy.Instance.OnEnvironmentReset event in Unity that loads the scene containing the robot.