Abstract
Multi-defender Stackelberg Security Games (MSSG) have recently gained increasing attention in the literature. However, the solutions offered to date are highly sensitive, wherein even small perturbations in the attacker's utility or slight uncertainties thereof can dramatically change the defenders' resulting payoffs and alter the equilibrium. In this paper, we introduce a robust model for MSSGs, which admits solutions that are resistant to small perturbations or uncertainties in the game's parameters. First, we formally define the notion of robustness, as well as the robust MSSG model. Then, for the non-cooperative setting, we prove the existence of a robust approximate equilibrium in any such game, and provide an efficient construction thereof. For the cooperative setting, we show that any such game admits a robust approximate α-core, provide an efficient construction thereof, and prove that stronger types of the core may be empty. Interestingly, the robust solutions can substantially increase the defenders' utilities over those of the non-robust ones.
Original language | English |
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Title of host publication | Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022 |
Editors | Luc De Raedt, Luc De Raedt |
Publisher | International Joint Conferences on Artificial Intelligence |
Pages | 433-439 |
Number of pages | 7 |
ISBN (Electronic) | 9781956792003 |
DOIs | |
State | Published - 2022 |
Event | 31st International Joint Conference on Artificial Intelligence, IJCAI 2022 - Vienna, Austria Duration: 23 Jul 2022 → 29 Jul 2022 |
Publication series
Name | IJCAI International Joint Conference on Artificial Intelligence |
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ISSN (Print) | 1045-0823 |
Conference
Conference | 31st International Joint Conference on Artificial Intelligence, IJCAI 2022 |
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Country/Territory | Austria |
City | Vienna |
Period | 23/07/22 → 29/07/22 |
Bibliographical note
Publisher Copyright:© 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.
Funding
∗This research has been partly supported by the Israel Science Foundation under grant 1958/20 and the EU Project TAILOR under grant 992215.
Funders | Funder number |
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European Commission | 992215 |
Israel Science Foundation | 1958/20 |