Szabo / Semeshenko / Castro | Resilient Complex Adaptive Systems | Buch | 978-1-394-32627-3 | www.sack.de

Buch, Englisch, 576 Seiten

Szabo / Semeshenko / Castro

Resilient Complex Adaptive Systems

Modeling, Simulation, Visualization and Engineering Approaches
1. Auflage 2026
ISBN: 978-1-394-32627-3
Verlag: John Wiley & Sons Inc

Modeling, Simulation, Visualization and Engineering Approaches

Buch, Englisch, 576 Seiten

ISBN: 978-1-394-32627-3
Verlag: John Wiley & Sons Inc


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.

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Weitere Infos & Material


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


Claudia Szabo, PhD, is aProfessor 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,

Saurabh Mittal, PhD, is a He has co-authored over publications including 5 books.

Viktoriya Semeshenko, PhD



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