Reachable Sets of Dynamic Systems: Uncertainty, Sensitivity, and Complex Dynamics introduces differential inclusions, providing an overview as well as multiple examples of its interdisciplinary applications. The design of dynamic systems of any type is an important issue as is the influence of uncertainty in model parameters and model sensitivity. The possibility of calculating the reachable sets may be a powerful additional tool in such tasks. This book can help graduate students, researchers, and engineers working in the field of computer simulation and model building, in the calculation of reachable sets of dynamic models.

A major objective of this monograph is to present an agent-based simulation of artificial populations. The focus is on possible unexpected or catastrophic events that may spontaneously appear in simulations. A short recall of the tenets of the theory of catastrophes is given. Several examples of artificial society simulations are provided as the main topic of the book. With agent-based modeling, possible catastrophes and unexpected events in artificial populations are simulated. The book presents a new modeling and simulation tool, applied to social system simulation. The models are coded in the object- and agent-oriented language Bluesss (Blues Simulation System), related to the C++ language. The program code consists of a series of generic declarations of processes. Each of them includes a number of events that are coded in C++. At the runtime, a population of objects is generated. All the objects (agents) start to execute their own events, and interact with one another. During the simulations it is possible to observe the macro-behavior of the population, where some unexpected or "catastrophic" events occur. The examples include a stock market crash, catastrophes in extended prey-predator systems, growing organisms and cancer, epidemics, social inequality and economic decay, mass-service systems, and more. Remarks on possible simultaneous events are also included.

This book presents examples of and the latest simulation studies on artificial societies and populations, highlighting innovative implementations of various models of artificial societies and populations using a new, C++-related simulation tool. It demonstrates that the prey-predator models-including spatial distribution, moving patterns, limited renewable food, fear, gregarious (herd) instinct, clustering, epidemics, and competition-are more complex than other publications have suggested, and highlights the great discrepancy between agent-based and conventional continuous models. The book also discusses the modeling and simulation of self-organization and interactions between organizations, including terror organizations, offering fascinating insights into organizational dynamics. The book provides a broad range of examples and comparisons with the classical dynamics approach, showing readers how to construct models of complex systems. It starts with descriptions of the behavior of interacting individuals and also includes important information on the macro-behavior of the whole system.

A major objective of this monograph is to present an agent-based simulation of artificial populations. The focus is on possible unexpected or catastrophic events that may spontaneously appear in simulations. A short recall of the tenets of the theory of catastrophes is given. Several examples of artificial society simulations are provided as the main topic of the book. With agent-based modeling, possible catastrophes and unexpected events in artificial populations are simulated. The book presents a new modeling and simulation tool, applied to social system simulation. The models are coded in the object- and agent-oriented language Bluesss (Blues Simulation System), related to the C++ language. The program code consists of a series of generic declarations of processes. Each of them includes a number of events that are coded in C++. At the runtime, a population of objects is generated. All the objects (agents) start to execute their own events, and interact with one another. During the simulations it is possible to observe the macro-behavior of the population, where some unexpected or "catastrophic" events occur. The examples include a stock market crash, catastrophes in extended prey-predator systems, growing organisms and cancer, epidemics, social inequality and economic decay, mass-service systems, and more. Remarks on possible simultaneous events are also included.

This book presents examples of and the latest simulation studies on artificial societies and populations, highlighting innovative implementations of various models of artificial societies and populations using a new, C++-related simulation tool. It demonstrates that the prey-predator models-including spatial distribution, moving patterns, limited renewable food, fear, gregarious (herd) instinct, clustering, epidemics, and competition-are more complex than other publications have suggested, and highlights the great discrepancy between agent-based and conventional continuous models. The book also discusses the modeling and simulation of self-organization and interactions between organizations, including terror organizations, offering fascinating insights into organizational dynamics. The book provides a broad range of examples and comparisons with the classical dynamics approach, showing readers how to construct models of complex systems. It starts with descriptions of the behavior of interacting individuals and also includes important information on the macro-behavior of the whole system.