Resilient Complex Adaptive Systems
Modeling, Simulation, Visualization and Engineering Approaches
1st Edition
Will be published approx. on 2. November 2026
Book
Hardback
576 pages
978-1-394-32627-3 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
Professional and scholarly
ISBN-13
978-1-394-32627-3 (9781394326273)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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.
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.
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.
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.
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.
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.
Content
1 Modeling and Simulation of Resilient Complex Adaptive Systems 2 Emergent Behavior in Resilient Complex Adaptive Systems: Challenges, Metrics and Engineering Approach
3 Epistemology of Resilient Complex Adaptive System Simulations
4 From ABM back to real data: time series visualization and model selection in the K+S agent-based model
5 Self-Aware Models with Explanatory Capabilities: Learning Explanatory Models from Simulation Experiments
6 Multi-agent Reinforcement Learning for Decision Making in Contested Environments
7 Intersectoral Labor Mobility in Argentina: Evolution and Resilience
8 A Novel Integrated Agent-Based Computational Economics and Multi-Agent Reinforcement Learning Framework: Application to Macrocrisis Phenomena
9 DEVS as a Method to Design Resilient Complex Adaptive Systems
10 A Framework For Characterizing, Understanding and Predicting Behavior in Complex Edge Computing Systems
11 Resilience-Aware Development Tools: Translating Resilience Concepts into Engineering Practice
12 Artificial Intelligence Networks: Structure, Dynamics, and Economics
13 Resilient Complex Adaptive Systems: A Communications Perspective
14 Scalable Rigidity Maintenance Strategies for Networked Multirobot Systems: Overcoming Decentralized Coordination Challenges
15 Immersive and Cognitive Urban Digital Twins for Sustainable and Resilient Smart Territories 16 The Role of Digital Twins in Improving River Water Quality
17 Integrating Simulation and Real-World Models for Harmful Algal and Cyanobacterial Blooms Management
18 Optimal Strategies to Contain and Prevent the Spread of Diseases in Group-structured Populations
19 Research Agenda for Resilient Complex Adaptive Systems Acronyms
3 Epistemology of Resilient Complex Adaptive System Simulations
4 From ABM back to real data: time series visualization and model selection in the K+S agent-based model
5 Self-Aware Models with Explanatory Capabilities: Learning Explanatory Models from Simulation Experiments
6 Multi-agent Reinforcement Learning for Decision Making in Contested Environments
7 Intersectoral Labor Mobility in Argentina: Evolution and Resilience
8 A Novel Integrated Agent-Based Computational Economics and Multi-Agent Reinforcement Learning Framework: Application to Macrocrisis Phenomena
9 DEVS as a Method to Design Resilient Complex Adaptive Systems
10 A Framework For Characterizing, Understanding and Predicting Behavior in Complex Edge Computing Systems
11 Resilience-Aware Development Tools: Translating Resilience Concepts into Engineering Practice
12 Artificial Intelligence Networks: Structure, Dynamics, and Economics
13 Resilient Complex Adaptive Systems: A Communications Perspective
14 Scalable Rigidity Maintenance Strategies for Networked Multirobot Systems: Overcoming Decentralized Coordination Challenges
15 Immersive and Cognitive Urban Digital Twins for Sustainable and Resilient Smart Territories 16 The Role of Digital Twins in Improving River Water Quality
17 Integrating Simulation and Real-World Models for Harmful Algal and Cyanobacterial Blooms Management
18 Optimal Strategies to Contain and Prevent the Spread of Diseases in Group-structured Populations
19 Research Agenda for Resilient Complex Adaptive Systems Acronyms