Computer Generation of Birds of a Feather Puzzles
Abstract
In this article, we describe a computer-aided design process for generating high-quality Birds of a Feather solitaire card puzzles. In each iteration, we generate puzzles via combinatorial optimization of an objective function. After solving and subjectively rating such puzzles, we compute objective puzzle features and regress our ratings onto such features to provide insight for objective function improvements. Through this iterative improvement process, we demonstrate the importance of the halfway solvability ratio in quality puzzle design. We relate our observations to recent work on tension in puzzle design, and suggest next steps for more efficient puzzle generation.
Cite
Text
Neller and Ziegler. "Computer Generation of Birds of a Feather Puzzles." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33019693Markdown
[Neller and Ziegler. "Computer Generation of Birds of a Feather Puzzles." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/neller2019aaai-computer/) doi:10.1609/AAAI.V33I01.33019693BibTeX
@inproceedings{neller2019aaai-computer,
title = {{Computer Generation of Birds of a Feather Puzzles}},
author = {Neller, Todd W. and Ziegler, Daniel},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2019},
pages = {9693-9699},
doi = {10.1609/AAAI.V33I01.33019693},
url = {https://mlanthology.org/aaai/2019/neller2019aaai-computer/}
}