Erschienen: 27.06.2019 Abbildung von Carmichael / Collins / Hadžikadic | Complex Adaptive Systems | 1st ed. 2019 | 2019 | Views from the Physical, Natur...

Carmichael / Collins / Hadžikadic

Complex Adaptive Systems

Views from the Physical, Natural, and Social Sciences

lieferbar ca. 10 Tage als Sonderdruck ohne Rückgaberecht

auch verfügbar als eBook (PDF) für 139.09 €

Buch. Hardcover

1st ed. 2019. 2019

viii, 250 S. 21 s/w-Abbildungen, 55 Farbabbildungen, Bibliographien

In englischer Sprache

Springer. ISBN 978-3-030-20307-8

Format (B x L): 15,5 x 23,5 cm

Gewicht: 513 g

Das Werk ist Teil der Reihe: Understanding Complex Systems

Produktbeschreibung

This book emerged out of international conferences organized as part of the AAAI Fall Symposia series, and the Swarmfest 2017 conference. It brings together researchers from diverse fields studying these complex systems using CAS and agent-based modeling tools and techniques. In the past, the knowledge gained in each domain has largely remained exclusive to that domain. By bringing together scholars who study these phenomena, the book takes knowledge from one domain to provide insight into others.
Most interesting phenomena in natural and social systems include constant transitions and oscillations among their various phases – wars, companies, societies, markets, and humans rarely stay in a stable, predictable state for long. Randomness, power laws, and human behavior ensure that the future is both unknown and challenging. How do events unfold? When do they take hold? Why do some initial events cause an avalanche while others do not? What characterizes these events? What are the thresholds that differentiate a sea change from a non-event?
Complex adaptive systems (CAS) have proven to be a powerful tool for exploring these and other related phenomena. The authors characterize a general CAS model as having a large number of self-similar agents that: 1) utilize one or more levels of feedback; 2) exhibit emergent properties and self-organization; and 3) produce non-linear dynamic behavior. Advances in modeling and computing technology have led not only to a deeper understanding of complex systems in many areas, but they have also raised the possibility that similar fundamental principles may be at work across these systems, even though the underlying principles may manifest themselves differently.

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