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

Analyze, design, and deploy resilient complex adaptive systems using MS&V

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.

Claudia Szabo, PhD, is a Professor leading the Complex Systems Research group at the University of Adelaide. She has authored over 100 papers spanning simulation, model driven engineering, systems of systems, self-adaptive systems, reinforcement learning, and multi-agent systems.

Rodrigo Castro, PhD, is a Professor in the Department of Computer Science at the University of Buenos Aires. He leads the Discrete Event Simulation Laboratory and is Deputy Director of the Computer Science Institute. He has over 30 years’ experience in the software industry with over 100 publications in modeling and simulation, including DEVS, Modelica, AI, hybrid and complex adaptive systems, spanning socio-natural and cyber-physical applications.

Viktoriya Semeshenko, PhD, is a Researcher leading the Complex Systems and Networks Laboratory (CSNetlab) at the Interdisciplinary Institute of Political Economy, University of Buenos Aires. She has authored over 30 publications applying network science, complexity, ABM and System Dynamics to socioeconomic systems, labor markets, and AI-driven structural change.

Saurabh Mittal, PhD, is a Director, JSE/SCARS at FlightSafety International. Previously, he was a Complex Systems Engineering – SME at Modern Technology Solution, Inc. and spent a decade as M&S SME at the MITRE Corporation. He has co-authored over 100 publications including 5 books covering DEVS, complex systems M&S, cyber-physical systems and cloud-enabled simulation systems.