Cooperative and Noncooperative Paradigms for Game-Theoretic Control of Socio-Technical Systems
For researchers in control, game theory, and network science, this tutorial provides a comprehensive overview of game-theoretic methods for socio-technical systems, but it is a survey without novel results.
This tutorial reviews cooperative and noncooperative game-theoretic frameworks for modeling, learning, and control in socio-technical systems, covering strategic, dynamic, and feedback-control approaches. It connects equilibrium analysis with adaptation and mechanism design, and discusses resilience and security challenges.
This tutorial presents cooperative and noncooperative game-theoretic frameworks for modeling, learning, and control in socio-technical systems, where human behavior, incentives, institutions, and social interactions are coupled with cyber-physical and networked infrastructures. The paper reviews strategic, dynamic, cooperative, matching, learning, and feedback-control approaches for analyzing how local decision-making, adaptation, and strategic interactions shape collective system outcomes. The tutorial further develops feedback-learning and incentive-design perspectives that connect equilibrium analysis with adaptation, distributed control, and mechanism design under information and coordination constraints. We also examine resilience and security challenges arising from adversarial behavior, misinformation, disruptions, and cascading failures in interconnected socio-technical networks. Finally, we discuss emerging research directions at the intersection of game theory, control, learning, and network science for resilient and adaptive socio-technical systems.