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{{Infobox Institute
|name= New England Complex Systems Institute
|founded= 1996
|location= [[Cambridge, MA]]
|address= 24 Mt. Auburn St. Cambridge, MA
|telephone= 617-547-4100
|fax= 617-661-7711
|website= [http://necsi.org/index.html necsi.org]
}}
The '''New England Complex Systems Institute''' (NECSI) is an American research institution dedicated to advancing the study of [[complex systems]]. It was founded in 1996 and is located in [[Cambridge, MA]].<ref name = "NECSI"> [http://necsi.org/index.html NECSI New England Complex Systems Institute], website 2007.</ref>
The '''New England Complex Systems Institute''' (NECSI) is an American research institution dedicated to advancing the study of [[complex systems]]. It was founded in 1996 and is located in [[Cambridge, MA]].<ref name = "NECSI"> [http://necsi.org/index.html NECSI New England Complex Systems Institute], website 2007.</ref>



Revision as of 08:33, 4 May 2009

New England Complex Systems Institute
Address24 Mt. Auburn St. Cambridge, MA
Location
Websitenecsi.org

The New England Complex Systems Institute (NECSI) is an American research institution dedicated to advancing the study of complex systems. It was founded in 1996 and is located in Cambridge, MA.[1]

Overview

NECSI was established by faculty of various New England academic institutions, to encourage communication and collaboration on these topics. Their take on "complex systems":[1]

Complex systems have multiple interacting components whose collective behavior cannot be simply inferred from the behavior of components. The recognition that understanding the parts cannot explain collective behavior has led to various new concepts and methodologies that are affecting all fields of science and engineering, and are being applied to technology, business and even social policy.

Areas of research

Evolution and Ecology

NECSI researchers have contributed to the understanding of evolutionary dynamics, the evolution of altruism, the origin and characterization of biodiversity, and the interplay between evolution and ecology.

Much of the work done at NECSI has focused on the role of the spatial distribution of species, an often overlooked factor of evolutionary dynamics. In the case where portions of a population are geographically isolated from each other, for example, Yaneer Bar-Yam was able to demonstrate shortcomings in the gene-centered view of evolution, an approximation that is valid only if there is complete mixing of alleles in the gene pool.[2]

Networks

Studies of network topologies have found surprising similarities between a variety of complex social, technological and biological networks. NECSI research in networks focuses on the relationship between structure, dynamics and function.

Representation

Complex systems exhibit behaviors at a variety of spatial and temporal scales. Researchers working at NECSI have developed a mathematical formalism for simultaneously describing systems on multiple scales. This formalism had been applied to physical systems, information systems, organizational behavior, engineering projects and military conflict.

An essential tool for multiscale analysis, the complexity profile, the relationship between the observed complexity of a system and the scale of observation.

Further fields of research

Faculty, co-faculty and affiliates

Faculty and Co-Faculty

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  • Mehran Kardar
  • Les Kaufman
  • Eric Klopfer
  • Blake LeBaron
  • Seth Lloyd
  • Tom Petzinger
  • Stuart Pimm
  • Daniel Rothman
  • Larry Rudolph

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Affiliates

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  • Marcus de Aguiar
  • Zvi Bar-Yam
  • Bruce Boghosian
  • Dan Braha
  • Raffaele Calabretta
  • Jeffrey Cares
  • Marshall Clemens
  • Gavin Crooks

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  • Meghan Dierks
  • Helen Harte
  • Steven Hassan
  • Sui Huang
  • Michael J. Jacobson
  • Fumiaki Katagiri
  • Andreas Kemper
  • Mark Klein

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  • David Meyer
  • Ali Minai
  • Hiroki Sayama
  • Tommaso Toffoli
  • Omer Trajman
  • Sheldon White
  • Uri Wilensky

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See also

References

  1. ^ a b NECSI New England Complex Systems Institute, website 2007.
  2. ^ Bar-Yam, Y. Formalizing the gene-centered view of evolution Adv. Complex Syst. 2 (3) 277-281 (1999).