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com.unity.ml-agents_1.0.0
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v0.1
ml-agents/ml-agents
GitHub
dffc37bf
Update to barracuda 1.3.3 and changes to the model inputs and outputs for LSTM (#5236)
* Initial commit * making it work with hallway. Added a new model version * addressing feedback * Adding a comment * formatting * modifying the changelog * Adding descriptions on the model version descriptions * Update com.unity.ml-agents/Runtime/Inference/GeneratorImpl.cs Co-authored-by: Chris Elion <chris.elion@unity3d.com> * addressing comments Co-authored-by: Chris Elion <chris.elion@unity3d.com> |
4 年前 | |
---|---|---|
.. | ||
mlagents | Update to barracuda 1.3.3 and changes to the model inputs and outputs for LSTM (#5236) | 4 年前 |
tests | Automatically generate samples based on placement of mlagents-sample.json files in our examples. (#5077) | 4 年前 |
README.md | [Release 16] Update Python and release versions (#5234) | 4 年前 |
setup.py | [docs] Update main doc references (#5251) | 4 年前 |
README.md
Unity ML-Agents Trainers
The mlagents
Python package is part of the
ML-Agents Toolkit. mlagents
provides a set of reinforcement and imitation learning algorithms designed to be
used with Unity environments. The algorithms interface with the Python API
provided by the mlagents_envs
package. See here for
more information on mlagents_envs
.
The algorithms can be accessed using the: mlagents-learn
access point. See
here for more information on using this
package.
Installation
Install the mlagents
package with:
python -m pip install mlagents==0.25.1
Usage & More Information
For more information on the ML-Agents Toolkit and how to instrument a Unity scene with the ML-Agents SDK, check out the main ML-Agents Toolkit documentation.
Limitations
mlagents
does not yet explicitly support multi-agent scenarios so training cooperative behavior among different agents is not stable.- Resuming self-play from a checkpoint resets the reported ELO to the default value.