1.

Record Nr.

UNINA9910820297703321

Autore

Miller John H (John Howard), <1959->

Titolo

Complex adaptive systems : an introduction to computational models of social life / / John H. Miller and Scott E. Page

Pubbl/distr/stampa

Princeton, N.J., : Princeton University Press, c2007

ISBN

1-282-45811-6

1-282-93635-2

9786612458118

9786612936357

1-4008-3552-6

0-691-12702-6

Edizione

[Course Book]

Descrizione fisica

1 online resource (284 p.)

Collana

Princeton studies in complexity

Classificazione

70.03

Altri autori (Persone)

PageScott E

Disciplina

300.1/513

Soggetti

Social systems - Mathematical models

Social sciences - Mathematical models

Sociale relaties

Computermodellen

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. [255]-260) and index.

Nota di contenuto

pt. 1. INTRODUCTION. Introduction -- Complexity in social worlds -- pt. 2. PRELIMINARIES. Modeling -- On emergence -- pt. 3. COMPUTATIONAL MODELING. Computation as theory -- Why agent-based objects? -- pt. 4. MODELS OF COMPLEX ADAPTIVE SOCIAL SYSTEMS. A basic framework -- Complex adaptive social systems in one dimension -- Social dynamics -- Evolving automata -- Some fundamentals of organizational decision making -- pt. 5. CONCLUSIONS. Social science in between -- Epilogue -- Appendixes. A. An open agenda for complex adaptive social systems -- B. Practices for computational modeling.

Sommario/riassunto

This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences.



Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.