ML Anthology

A Monte Carlo Tree Search Player for Birds of a Feather Solitaire

Christian Roberson, Katarina Sperduto
AAAI 2019 pp. 9700-9705
doi:10.1609/AAAI.V33I01.33019700 /aaai/2019/roberson2019aaai-monte/

Abstract

Artificial intelligence in games serves as an excellent platform for facilitating collaborative research with undergraduates. This paper explores several aspects of a research challenge proposed for a newly-developed variant of a solitaire game. We present multiple classes of game states that can be identified as solvable or unsolvable. We present a heuristic for quickly finding goal states in a game state search tree. Finally, we introduce a Monte Carlo Tree Search-based player for the solitaire variant that can win almost any solvable starting deal efficiently.

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Cite

Text

Roberson and Sperduto. "A Monte Carlo Tree Search Player for Birds of a Feather Solitaire." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33019700

Markdown

[Roberson and Sperduto. "A Monte Carlo Tree Search Player for Birds of a Feather Solitaire." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/roberson2019aaai-monte/) doi:10.1609/AAAI.V33I01.33019700

BibTeX

@inproceedings{roberson2019aaai-monte,
  title     = {{A Monte Carlo Tree Search Player for Birds of a Feather Solitaire}},
  author    = {Roberson, Christian and Sperduto, Katarina},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2019},
  pages     = {9700-9705},
  doi       = {10.1609/AAAI.V33I01.33019700},
  url       = {https://mlanthology.org/aaai/2019/roberson2019aaai-monte/}
}