Source: openai-gym
Section: python
Priority: optional
Maintainer: Adam Cecile <acecile@le-vert.net>
Build-Depends: debhelper (>= 9), dh-python, python-all, python-setuptools, python3-all, python3-setuptools,
  python3-scipy, python-scipy,
  python3-numpy (>= 1:1.11.0~), python-numpy (>= 1:1.11.0~),
  python3-requests (>= 2.0~), python3-requests (>= 2.0~),
  python3-six, python-six,
  python3-pyglet (>= 1.2.0~), python-pyglet (>= 1.2.0~),
  python3-pytest (>= 3~) <!nocheck>, python-pytest (>= 3~) <!nocheck>,
  python3-box2d <!nocheck>, python-box2d <!nocheck>,
  python3-opengl <!nocheck>, python-opengl <!nocheck>,
  ffmpeg <!nocheck>,
  xauth <!nocheck>, xvfb <!nocheck>, libgl1-mesa-dri <!nocheck>,
  lsb-release,
Standards-Version: 3.9.8
Homepage: https://gym.openai.com/
X-Python-Version: >= 2.7
X-Python3-Version: >= 3.4

Package: python-gym
Architecture: any
Depends: ${python:Depends}, ${misc:Depends}
Description: Develop and compare reinforcement learning algorithms (Python 2)
 Gym is a toolkit for developing and comparing reinforcement learning
 algorithms.
 .
 It makes no assumptions about the structure of your agent, and is compatible
 with any numerical computation library, such as TensorFlow or Theano.
 .
 The gym library is a collection of test problems environments that you can
 use to work out your reinforcement learning algorithms.
 .
 These environments have a shared interface, allowing you to write general
 algorithms.
 .
 This package installs the library for Python 2.

Package: python3-gym
Architecture: any
Depends: ${python3:Depends}, ${misc:Depends}
Description: Develop and compare reinforcement learning algorithms (Python 3)
 Gym is a toolkit for developing and comparing reinforcement learning
 algorithms.
 .
 It makes no assumptions about the structure of your agent, and is compatible
 with any numerical computation library, such as TensorFlow or Theano.
 .
 The gym library is a collection of test problems environments that you can
 use to work out your reinforcement learning algorithms.
 .
 These environments have a shared interface, allowing you to write general
 algorithms.
 .
 This package installs the library for Python 3.
