This book aims to provide a description of these new Artificial Intelligence technologies and approaches to the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field such as the platforms and/or the software tools for smart modeling and simulating complex systems. These tasks are difficult to accomplish using traditional computational approaches due to the complex relationships of components and distributed features of resources, as well as the dynamic work environments. In order to effectively model the complex systems, intelligent technologies such as multi-agent systems and smart grids are employed to model and simulate the complex systems in the areas of ecosystem, social and economic organization, web-based grid service, transportation systems, power systems and evacuation systems.

Providing a comprehensive overview of the modeling of complex systems, with particular emphasis on the collective aspects of these systems, this book situates itself at the forefront of available literature. Exemplifying practically Wolfram’s theses found in A New Kind of Science, discussions center on where it is best to use a cellular automaton, when it is reasonable to use a hybrid approach, and when it is best to use a traditional method such as one based on differential equations. A range of fascinating examples are discussed, ranging from models of crowd dynamics, car traffic, downhill skiers and oil spreading across the sea surface. All are discussed and illustrated with comments. These examples explore how simple rules can create incredibly complex patterns and are used to compare cellular automata with more traditional methods. This book is of critical importance to students and lecturers interested in complex system modeling as well as containing translatable techniques that have applications in a wide range of fields

Introduction to Intelligent Simulation of Complex Discrete Systems and Processes: RAO Language focuses on a unique approach in modeling and simulation of complex systems. In this volume are considered features of complex systems and processes, their mathematical description, and modeling. Theoretical foundations of the RAO (Resource-Action-Operation) language as well as its syntax and utilisation are given. Examples of simulation models of different complexity levels, related to different fields, are also presented. The RAO intelligent modeling system, introduced and described in Introduction to Intelligent Simulation of Complex Discrete Systems and Processes is unique because: (1) it makes simulation modeling universal for the classes of systems and processes modeled; (2) it is simple to modify the models; and (3) it has the capacity to model complex control systems together with the object controlled (including simulation modeling for on-line control). The RAO tool allows the user to use a language very similar to his professional language and rids him of intermediary, supplementary description of the system modeled. In fifteen chapters this volume provides an overview of general modeling trends, and hence serves the research community in guiding their modeling methods; intelligent simulation modeling is introduced to solve complex systems and processes.

This illuminating text/reference presents a review of the key aspects of the modeling and simulation (M&S) life cycle, and examines the challenges of M&S in different application areas. The authoritative work offers valuable perspectives on the future of research in M&S, and its role in engineering complex systems. Topics and features: reviews the challenges of M&S for urban infrastructure, healthcare delivery, automated vehicle manufacturing, deep space missions, and acquisitions enterprise; outlines research issues relating to conceptual modeling, covering the development of explicit and unambiguous models, communication and decision-making, and architecture and services; considers key computational challenges in the execution of simulation models, in order to best exploit emerging computing platforms and technologies; examines efforts to understand and manage uncertainty inherent in M&S processes, and how these can be unified under a consistent theoretical and philosophical foundation; discusses the reuse of models and simulations to accelerate the simulation model development process. This thought-provoking volume offers important insights for all researchers involved in modeling and simulation across the full spectrum of disciplines and applications, defining a common research agenda to support the entire M&S research community.

Complexity science aims to better understand the processes of both natural and man-made systems which are composed of many interacting entities at different scales. A disaggregated approach is proposed for simulating electricity systems, by using agent-based models coupled to continuous ones. The approach can help in acquiring a better understanding of the operation of the system itself, e.g. on emergent phenomena or scale effects; as well as in the improvement and design of future smart grids.

Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the “General Reference Model for Agent-based Modeling and Simulation” (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models –from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hardware resources in an optimized fashion.

This four-volume set (CCIS 643, 644, 645, 646) constitutes the refereed proceedings of the 16th Asia Simulation Conference and the First Autumn Simulation Multi-Conference, AsiaSim / SCS AutumnSim 2016, held in Beijing, China, in October 2016. The 265 revised full papers presented were carefully reviewed and selected from 651 submissions. The papers in this first volume of the set are organized in topical sections on modeling and simulation theory and methodology; model engineering for system of systems; high performance computing and simulation; modeling and simulation for smart city.