CITATION.cff

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cff-version: 1.2.0
title: >-
  Tetris Gymnasium: A Modular Reinforcement Learning
  Environment for Tetris
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Maximilian
    family-names: Weichart
    affiliation: University of Regensburg
  - given-names: Philipp
    family-names: Hartl
    affiliation: University of Regensburg
identifiers:
  - type: url
    value: 'https://easychair.org/publications/preprint/154Q'
repository-code: 'https://github.com/Max-We/Tetris-Gymnasium'
url: 'https://max-we.github.io/Tetris-Gymnasium/'
abstract: >-
  Tetris Gymnasium is a modern Reinforcement Learning (RL)
  environment for Tetris, built with Gymnasium. It addresses
  the limitations of existing Tetris environments by being
  modular, understandable, and adjustable. This environment
  fulfills all requirements of a feature-complete RL
  environment while being adaptable to various research
  needs.
keywords:
  - reinforcement learning
  - tetris
  - machine learning
  - artificial intelligence
  - gymnasium
license: MIT
version: '2'
date-released: '2024-07-20'