Catastrophes and Unexpected Behavior Patterns in Complex Artificial Populations (Hardcover, 1st ed. 2021)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Evolutionary Economics and Social Complexity Science, 27
Release date:	July 2021
First published:	2021
Authors:	Stanislaw Raczynski
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	184
Edition:	1st ed. 2021
ISBN-13:	978-981-16-2573-2
Categories:	Books > Social sciences > Education > General Books > Business & Economics > Economics > Economic theory & philosophy Books > Computing & IT > Applications of computing > Computer modelling & simulation Promotions
LSN:	981-16-2573-5
Barcode:	9789811625732

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