Efficiently Solving Joint Activity Based Security Games

Shieh, Eric Anyung (University of Southern California) | Jain, Manish (University of Southern California) | Jiang, Albert Xin (University of Southern California) | Tambe, Milind (University of Southern California)

AAAI Conferences 

Despite recent successful real-world deployments of Stackelberg Security Games (SSGs), scale-up remains a fundamental challenge in this field. The latest techniques do not scale-up to domains where multiple defenders must coordinate time-dependent joint activities. To address this challenge, this paper presents two branch-and-price algorithms for solving SSGs, SMARTO and SMARTH, with three novel features: (i) a column-generation approach that uses an ordered network of nodes (determined by solving the traveling salesman problem) to generate individual defender strategies; (ii) exploitation of iterative reward shaping of multiple coordinating defender units to generate coordinated strategies; (iii) generation of tighter upper-bounds for pruning by solving security games that only abide by key scheduling constraints. We provide extensive experimental results and formal analyses.

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