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BRAID: Learning Equilibrium Maps in Interdependent Security Games via Weight-Tied Iterative Graph Neural Networks

Year: 2026

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-032-40367-4_26

Authors: Elnaz Nowrouzi, Zhiqun Zuo, Xueru Zhang, Mohammad Mahdi Khalili

Institution: The Ohio State University

Language: English

Topic: Game Theory and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

Funders: National Science Foundation, Division of Civil, Mechanical and Manufacturing Innovation

Awards: Collaborative Research: FW-HTF-R: Future of Construction Workplace Health Monitoring, Collaborative Research: RI: AF: Small: Long-Term Impact of Fair Machine Learning under Strategic Individual Behavior, Collaborative Research: RI: AF: Small: Long-Term Impact of Fair Machine Learning under Strategic Individual Behavior, MATH-DT: Heterogeneous transfer and federated learning for digital twin in unmanned aerial vehicles, Collaborative Research: SLES: Long-Term Safety for Human-AI Ecosystem

OpenAlex ID: W7203686773

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