Resilient Complex Adaptive Systems: Modeling, Simulation, Visualization and Engineering Approaches

Resilient Complex Adaptive Systems: Modeling, Simulation, Visualization and Engineering Approaches demonstrates how modeling, simulation, and visualization facilitate the analysis, design, implementation, and deployment of resilient CAS. Across 17 chapters, this edited volume examines existing research from multiple perspectives, addressing emergent behavior, control and decision making, and utilization of advanced analytics using AI and machine learning with practical examples throughout.

The volume captures lessons learned from CAS modeling across application domains including economics, crisis management, biology, Internet of Things, defense, and ecology. Four structured goals guide readers from domain-specific MS&V foundations through emergent behavior design approaches and AI/ML-enabled analytics to the formulation of functional and resilient CAS engineering principles.

Readers will also find:

• Approaches for leveraging AI and machine learning to support control and decision making within resilient complex adaptive systems
• Multi-domain case studies spanning economics, defense, ecology, biology, and crisis management that illustrate CAS modeling techniques
• Methods for designing emergent behavior properties in systems of interacting agents using state-of-the-art simulation frameworks
• Engineering approaches that extend acquired modeling knowledge toward building functional CAS with targeted resilience characteristics
• Visualization techniques that support analysis of global-level properties arising from agent-based complex adaptive system interactions

Designed for researchers, lecturers, and graduate students in computer science, systems engineering, and computer engineering, this book also serves practitioners, program managers, research directors, and policy makers who require rigorous MS&V frameworks for understanding and engineering resilient complex adaptive systems.