{"type":"ScholarlyArticle","title":"Beyond Homogeneous Adversaries: Stackelberg Security Games with Mixed Quantal Response","authors":[{"name":"Hoang Giang Pham","slug":"hoang-giang-pham","given":"Hoang Giang","family":"Pham","affiliation":""},{"name":"Tien Mai","slug":"tien-mai","given":"Tien","family":"Mai","affiliation":""},{"name":"Thuy Anh Ta","slug":"thuy-anh-ta","given":"Thuy Anh","family":"Ta","affiliation":""},{"name":"Minh Hoàng Hà","slug":"minh-hoang-ha","given":"Minh Hoàng","family":"Hà","affiliation":""}],"abstract":"The quantal response (QR) model is widely used in Stackelberg security games (SSGs) to capture boundedly rational adversaries. Existing work on SSGs under QR, however, almost exclusively assumes a homogeneous attacker population, ignoring heterogeneity in attacker preferences and rationality. We study SSG with mixed quantal response attackers, where the follower population consists of multiple discrete attacker types, each following a type-specific QR model. The defender allocates limited resources across targets, while an attacker drawn from this heterogeneous population observes the defender’s strategy and attacks a single target. This results in a highly non-convex equilibrium computation problem. We develop a polynomial-time approximation scheme (PTAS) for this setting when the number of attacker types is bounded, based on an exponential cone programming formulation combined with a carefully designed Branch-and-Bound procedure. Experiments demonstrate that our approach outperforms standard gradient-based methods and that explicitly modeling attacker heterogeneity yields significant gains over traditional SSG models with a single QR attacker.","doi":"10.24963/ijcai.2026/392","url":"https://ijcai.org/proceedings/2026/392","pdf":"https://ijcai.org/proceedings/2026/0392.pdf","markdown":"https://ijcai.org/proceedings/2026/392.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/392","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Game Theory and Economic Paradigms","track":"Main Track","number":392,"pages":{"first":3523,"last":3531},"keywords":["Game Theory and Economic Paradigms: Noncooperative games"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}