ppo-mujoco-halfcheetah/pyproject.toml at main · giansimone/ppo-mujoco-halfcheetah · GitHub

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[tool.poetry]
name = "ppo-mujoco-halfcheetah"
version = "0.1.0"
description = "A PyTorch implementation of Proximal Policy Optimization (PPO) for training an agent to solve the HalfCheetah-v5 environment from Gymnasium using MuJoCo."
authors = ["Giansimone Perrino <hello@giansimone.dev>"]
license = "MIT"
readme = "README.md"
repository = "https://github.com/giansimone/ppo-mujoco-halfcheetah"
packages = [
    { include = "ppo_mujoco_halfcheetah" }
]
keywords = [
    "reinforcement-learning",
    "deep-reinforcement-learning",
    "proximal-policy-optimization",
    "ppo",
    "mujoco",
    "gymnasium",
    "halfcheetah",
    "pytorch",
]
classifiers = [
    "Programming Language :: Python :: 3.13",
    "License :: OSI Approved :: MIT License",
    "Operating System :: OS Independent",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]

[tool.poetry.dependencies]
python = ">=3.13,<3.14"
torch = "^2.9.0"
gymnasium = {extras = ["mujoco"], version = "^1.2.1"}
pyyaml = "^6.0.3"
huggingface-hub = "^1.1.2"
imageio = {extras = ["ffmpeg"], version = "^2.37.2"}


[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"