Bayesian Repeated Zero-Sum Games with Persistent State, with Application to Security Games
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Conitzer, V; Deng, Y; Dughmi, S
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2020
We study infinitely-repeated two-player zero-sum games with one-sided private information and a persistent state. Here, only one of the two players learns the state of the repeated game. We consider two models: either the state is chosen by nature, or by one of the players. For the former, the equilibrium of the repeated game is known to be equivalent to that of a one-shot public signaling game, and we make this equivalence algorithmic. For the latter, we show equivalence to one-shot team max-min games, and also provide an algorithmic reduction. We apply this framework to repeated zero-sum security games with private information on the side of the defender and provide an almost complete characterization of their computational complexity.
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Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
ISBN
9783030649456
Publication Date
January 1, 2020
Volume
12495 LNCS
Start / End Page
444 / 458
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
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Conitzer, V., Deng, Y., & Dughmi, S. (2020). Bayesian Repeated Zero-Sum Games with Persistent State, with Application to Security Games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12495 LNCS, pp. 444–458). https://doi.org/10.1007/978-3-030-64946-3_31
Conitzer, V., Y. Deng, and S. Dughmi. “Bayesian Repeated Zero-Sum Games with Persistent State, with Application to Security Games.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12495 LNCS:444–58, 2020. https://doi.org/10.1007/978-3-030-64946-3_31.
Conitzer V, Deng Y, Dughmi S. Bayesian Repeated Zero-Sum Games with Persistent State, with Application to Security Games. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. p. 444–58.
Conitzer, V., et al. “Bayesian Repeated Zero-Sum Games with Persistent State, with Application to Security Games.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12495 LNCS, 2020, pp. 444–58. Scopus, doi:10.1007/978-3-030-64946-3_31.
Conitzer V, Deng Y, Dughmi S. Bayesian Repeated Zero-Sum Games with Persistent State, with Application to Security Games. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. p. 444–458.
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
ISBN
9783030649456
Publication Date
January 1, 2020
Volume
12495 LNCS
Start / End Page
444 / 458
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences