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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Página 23
... random null model. A theoretical expectation for the average number of neighbors in the bidder net- work is given by 〈k〉= 2(〈b) − 1)〈a〉= 14 where 〈b〉 is the average number of bidders per auction and 〈a〉 is the average number ...
... random null model. A theoretical expectation for the average number of neighbors in the bidder net- work is given by 〈k〉= 2(〈b) − 1)〈a〉= 14 where 〈b〉 is the average number of bidders per auction and 〈a〉 is the average number ...
Página 24
... random null model (RNM) obtained by reshuffling the bidders in different auctions and the reduced version of the network used for cluster analysis containing only those bidders having taken part in more than one auction number of nodes ...
... random null model (RNM) obtained by reshuffling the bidders in different auctions and the reduced version of the network used for cluster analysis containing only those bidders having taken part in more than one auction number of nodes ...
Página 25
... random assignment of bidders into groups of the same size and degree distribution and is given by [ mss ] = K2 / 4M . By K s we denote the total number of links emanating from members of group s , while M is the total number of links in ...
... random assignment of bidders into groups of the same size and degree distribution and is given by [ mss ] = K2 / 4M . By K s we denote the total number of links emanating from members of group s , while M is the total number of links in ...
Página 26
... random . The order of the groups was chosen to optimally show the correspondence between the ordering resulting from the γ = 0.5 and the γ 1 ordering . In this representation , link densities correspond to pixel densities and thus to ...
... random . The order of the groups was chosen to optimally show the correspondence between the ordering resulting from the γ = 0.5 and the γ 1 ordering . In this representation , link densities correspond to pixel densities and thus to ...
Página 28
... random graphs will cluster into equal sized communities and calculate that a random graph with the same number of nodes and links, i.e. disregarding the scale free degree distribution and the affiliation network structure of the graph ...
... random graphs will cluster into equal sized communities and calculate that a random graph with the same number of nodes and links, i.e. disregarding the scale free degree distribution and the affiliation network structure of the graph ...
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 |
Path Length Scaling and Discrete Effects in Complex | 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 |
Palavras e frases frequentes
adjacency matrix agents algorithm analysis applied approach autonomy average bankruptcy behavior bidders bidding factor bounded rationality capacity carrier cluster clustering coefficient coefficient communication competitors complex systems computational connected cost customers cycle decision defined degree distribution delay demand density distribution eBay economic effect enterprise evolution example factory fictitious play FIFO Figure firm flow forecast function global graph groups Helbing increase input Intel interactions Internet Governance Forum jam front logistics lots manufacturing methods nodes operational opinion space optimization oscillations output paradigm parameter performance Phys players power law predict probability problem production profit random random graphs recommendation system reinforcement learning represents robustness scale-free networks scenario second price auction self-organization semiconductor server shipment simulation social network strategies structure suppliers tion tool topological traffic Transportation trust users vehicles
Passagens conhecidas
Página 65 - By preferring the support of domestic to that of foreign industry, he intends only his own security; and by directing that industry in such a manner as its produce may be of the greatest value, he intends only his own gain, and he is in this, as in many other cases, led by an invisible hand to promote an end which was no part of his intention.
Página 137 - a market institution with an explicit set of rules determining resource allocation and prices on the basis of bids from the market participants".
Página 35 - Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA 99 (2002) 7821-7826 [15] Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., Parisi, D.: Defining and identifying communities in networks.
Página 222 - The rest of the chapter is organised as follows: in Section 2, we analyze the role of FDI in export-oriented industrialisation.
Página 118 - Simulation methods for studying nonstationary behavior of computer networks," IEEE Journal on Selected Areas in Communications, Vol. 8, No. 9, pp. 1696-1708, December 1990 [2] JA Garay and IS Copal, "Call preemption in communication networks," Proceedings of INFOCOM '92, pp.
Página 174 - Deciding between the common and private value paradigms in empirical models of auctions.
Página 21 - We conclude with a discussion of the implications of these findings for the growth potential of online vendors.