Cooperative and Noncooperative Paradigms for Game-Theoretic Control of Socio-Technical Systems

TL;DR

This tutorial explores game-theoretic frameworks for modeling, analyzing, and controlling socio-technical systems, addressing strategic interactions, incentives, resilience, and security challenges.

Contribution

It reviews and develops approaches connecting equilibrium analysis with adaptive control, incentive design, and resilience in socio-technical networks.

Findings

Analyzes strategic, dynamic, and cooperative interactions in socio-technical systems.

Develops feedback-learning and incentive-design methods for system control.

Examines security and resilience issues due to adversarial behaviors and disruptions.

Abstract

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.