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Author:
Alexander Nasuta
License:
MIT License Copyright (c) 2025 Alexander Nasuta Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to ...
Summary:
A minimalistic implementation of the Monte Carlo Tree Search algorithm for planning problems fomulated as gymnaisum reinforcement learning environments.
Latest version:
1.5.1
Required dependencies:
gymnasium
|
matplotlib
|
numpy
|
rich
Optional dependencies:
flake8
|
furo
|
graph-jsp-env
|
graph-matrix-jsp-env
|
jsp-instance-utils
|
jssenv
|
jupyter
|
jupytext
|
mypy
|
myst-parser
|
nbsphinx
|
pandoc
|
pip-tools
|
pytest
|
pytest-cov
|
sphinx
|
sphinx-autobuild
|
sphinx-copybutton
|
stable_baselines3
|
twine
|
typing_extensions
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