ML Anthology

Hustling in Repeated Zero-Sum Games with Imperfect Execution

Christopher Archibald, Yoav Shoham
IJCAI 2011 pp. 31-36
doi:10.5591/978-1-57735-516-8/IJCAI11-017 /ijcai/2011/archibald2011ijcai-hustling/

Abstract

We study repeated games in which players have imperfect execution skill and one player's true skill is not common knowledge. In these settings the possibility arises of a player "hustling," or pretending to have lower execution skill than they actually have. Focusing on repeated zero-sum games, we provide a hustle-proof strategy; this strategy maximizes a player's payoff, regardless of the true skill level of the other player.

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Text

Archibald and Shoham. "Hustling in Repeated Zero-Sum Games with Imperfect Execution." International Joint Conference on Artificial Intelligence, 2011. doi:10.5591/978-1-57735-516-8/IJCAI11-017

Markdown

[Archibald and Shoham. "Hustling in Repeated Zero-Sum Games with Imperfect Execution." International Joint Conference on Artificial Intelligence, 2011.](https://mlanthology.org/ijcai/2011/archibald2011ijcai-hustling/) doi:10.5591/978-1-57735-516-8/IJCAI11-017

BibTeX

@inproceedings{archibald2011ijcai-hustling,
  title     = {{Hustling in Repeated Zero-Sum Games with Imperfect Execution}},
  author    = {Archibald, Christopher and Shoham, Yoav},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2011},
  pages     = {31-36},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-017},
  url       = {https://mlanthology.org/ijcai/2011/archibald2011ijcai-hustling/}
}