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Designing the game to play: Optimizing payoff structure in security games

Designing the game to play: Optimizing payoff structure in security games
Designing the game to play: Optimizing payoff structure in security games

We study Stackelberg Security Games where the defender, in addition to allocating defensive resources to protect targets from the attacker, can strategically manipulate the attacker's payoff under budget constraints in weighted Lp-norm form regarding the amount of change. For the case of weighted L1-norm constraint, we present (i) a mixed integer linear program-based algorithm with approximation guarantee; (ii) a branch-and-bound based algorithm with improved efficiency achieved by effective pruning; (iii) a polynomial time approximation scheme for a special but practical class of problems. In addition, we show that problems under budget constraints in L0 and weighted Lnorm form can be solved in polynomial time.

512-518
International Joint Conferences on Artificial Intelligence
Shi, Zheyuan Ryan
08843b07-26a0-4aa0-9f8b-3c8f929933d5
Tang, Ziye
28d38245-3f13-4590-b038-0342f9f544fc
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Singh, Rohit
53e6cf06-26c9-469d-8ccc-886831e45df1
Fang, Fei
0be9695c-e812-4001-86e3-3ec3b553a3aa
Shi, Zheyuan Ryan
08843b07-26a0-4aa0-9f8b-3c8f929933d5
Tang, Ziye
28d38245-3f13-4590-b038-0342f9f544fc
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Singh, Rohit
53e6cf06-26c9-469d-8ccc-886831e45df1
Fang, Fei
0be9695c-e812-4001-86e3-3ec3b553a3aa

Shi, Zheyuan Ryan, Tang, Ziye, Tran-Thanh, Long, Singh, Rohit and Fang, Fei (2018) Designing the game to play: Optimizing payoff structure in security games. In Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018. vol. 2018-July, International Joint Conferences on Artificial Intelligence. pp. 512-518 .

Record type: Conference or Workshop Item (Paper)

Abstract

We study Stackelberg Security Games where the defender, in addition to allocating defensive resources to protect targets from the attacker, can strategically manipulate the attacker's payoff under budget constraints in weighted Lp-norm form regarding the amount of change. For the case of weighted L1-norm constraint, we present (i) a mixed integer linear program-based algorithm with approximation guarantee; (ii) a branch-and-bound based algorithm with improved efficiency achieved by effective pruning; (iii) a polynomial time approximation scheme for a special but practical class of problems. In addition, we show that problems under budget constraints in L0 and weighted Lnorm form can be solved in polynomial time.

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More information

Published date: 2018
Venue - Dates: 27th International Joint Conference on Artificial Intelligence, Stockholm, Sweden, 2018-07-13 - 2018-07-19

Identifiers

Local EPrints ID: 426543
URI: https://eprints.soton.ac.uk/id/eprint/426543
PURE UUID: 27eda364-1a3c-40d4-b066-721c020655ad
ORCID for Long Tran-Thanh: ORCID iD orcid.org/0000-0003-1617-8316

Catalogue record

Date deposited: 30 Nov 2018 17:30
Last modified: 20 Jul 2019 00:48

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Contributors

Author: Zheyuan Ryan Shi
Author: Ziye Tang
Author: Long Tran-Thanh ORCID iD
Author: Rohit Singh
Author: Fei Fang

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