A Highly-Parameterized Ensemble to Play Gin Rummy

Masayuki Nagai, Kavya Shrivastava, Kien Ta, Steven Bogaerts, Chad Byers

AAAI 2021 pp. 15614-15621

doi:10.1609/AAAI.V35I17.17839 /aaai/2021/nagai2021aaai-highly/

Abstract

This paper describes the design and training of a computer Gin Rummy player. The system includes three main components to make decisions about drawing cards, discarding, and ending the game, with numerous parameters controlling behavior. In particular, an ensemble approach is explored in the discard decision. Finally, three sets of parameter tuning and performance experiments are analyzed.

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Cite

Text

Nagai et al. "A Highly-Parameterized Ensemble to Play Gin Rummy." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I17.17839

Markdown

[Nagai et al. "A Highly-Parameterized Ensemble to Play Gin Rummy." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/nagai2021aaai-highly/) doi:10.1609/AAAI.V35I17.17839

BibTeX

@inproceedings{nagai2021aaai-highly,
  title     = {{A Highly-Parameterized Ensemble to Play Gin Rummy}},
  author    = {Nagai, Masayuki and Shrivastava, Kavya and Ta, Kien and Bogaerts, Steven and Byers, Chad},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {15614-15621},
  doi       = {10.1609/AAAI.V35I17.17839},
  url       = {https://mlanthology.org/aaai/2021/nagai2021aaai-highly/}
}