Managing Complexity: Insights, Concepts, ApplicationsDirk Helbing Springer, 13/10/2007 - 393 páginas Each chapter in Managing Complexity focuses on analyzing real-world complex systems and transferring knowledge from the complex-systems sciences to applications in business, industry and society. The interdisciplinary contributions range from markets and production through logistics, traffic control, and critical infrastructures, up to network design, information systems, social conflicts and building consensus. They serve to raise readers' awareness concerning the often counter-intuitive behavior of complex systems and to help them integrate insights gained in complexity research into everyday planning, decision making, strategic optimization, and policy. Intended for a broad readership, the contributions have been kept largely non-technical and address a general, scientifically literate audience involved in corporate, academic, and public institutions. |
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... behavior the manifestations of which are the spontaneous formation of distinctive temporal, spatial or functional structures. Models of such systems can be successfully mapped onto quite diverse “real-life” situations like the climate ...
... behavior of which they are capable. The Springer Series in Understanding Complex Systems series (UCS) promotes new ... behavioral, economic, neuroand cognitive sciences (and derivatives thereof); second, to encourage novel applications ...
... behavior of complex systems to various fields of practical applications. At the same time, it intends to stimulate more intensive research in this promising and important area of science in the future. The presentation is oriented at a ...
... behavior is often found close to the equilibrium state of a system. However, when complex systems are driven far from equilibrium, non-linearities dominate, which can cause many kinds of “strange” and counter-intuitive behaviors. In the ...
... behavior of chaotic systems unpredictable (beyond a certain time horizon), see Fig. 3. 1.2 Self-Organization, Competition, and Cooperation Systems with non-linear interactions do not necessarily behave chaotically. Often, they are ...
Índice
1 | |
18 | |
Managing Autonomy and Control in Economic Systems | 37 |
The Illusion of Control | 57 |
Benefits and Drawbacks of Simple Models for Complex | 89 |
Coping with Nonlinearity and Complexity | 119 |
Repeated Auction Games and Learning Dynamics | 137 |
Decentralized Approaches to Adaptive Traffic Control | 177 |
Stefano Battiston Domenico Delli Gatti Mauro Gallegati 219 | 241 |
Bootstrapping the Long Tail in Peer to Peer Systems | 262 |
Complexity in Human Conflict | 303 |
Fostering Consensus in Multidimensional Continuous Opinion | 321 |
MultiStakeholder Governance Emergence | 335 |
Evolutionary Engineering of Complex Functional Networks | 350 |
Julian Sienkiewicz Agata Fronczak Piotr Fronczak Krzysztof | 369 |
Index | 389 |
Arne Kesting Martin Schönhof Stefan Lämmer Martin Treiber | 201 |
Trade Credit Networks and Systemic Risk | 218 |
Outras edições - Ver tudo
Managing Complexity: Insights, Concepts, Applications Dirk Helbing Pré-visualização indisponível - 2007 |
Managing Complexity: Insights, Concepts, Applications Dirk Helbing Pré-visualização indisponível - 2010 |