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com.unity.ml-agents_1.0.0
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com.unity.ml-agents_1.0.3
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latest_release
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v0.1
ml-agents/ml-agents
GitHub
95efe03b
[MLA-1519] Don't mark action_probs as an output node. (#4613)
* remove action_probs from output nodes * changelog * pin cattrs upper version * print pip freeze results * add comment about cattrs version |
4 年前 | |
|---|---|---|
| .. | ||
| mlagents | [MLA-1519] Don't mark action_probs as an output node. (#4613) | 4 年前 |
| tests | Add ActionSpec (#4586) | 4 年前 |
| README.md | [refactor] Store and restore state along with checkpoints (#4025) | 5 年前 |
| setup.py | [MLA-1519] Don't mark action_probs as an output node. (#4613) | 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:
pip3 install mlagents
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
mlagentsdoes 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.