Bigger than Chaos

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A01=Michael Strevens
Author_Michael Strevens
biology and probability
Category=PDA
Category=QD
chaotic behavior
coarse graining
complex systems
complexity science
econophysics
ecosystem dynamics
emergence
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
equilibrium states
foundations of probability
large scale patterns
lawlike behavior
macrobehavior
mathematical modeling
microbehavior
nonlinear systems
philosophy of science
physics and probability
population ecology
predictability
probabilistic independence
probability
randomness and order
simplicity from complexity
statistical mechanics
statistical reasoning
stochastic processes
systems theory
thermodynamics

Product details

  • ISBN 9780674022591
  • Weight: 544g
  • Dimensions: 144 x 227mm
  • Publication Date: 01 Sep 2006
  • Publisher: Harvard University Press
  • Publication City/Country: US
  • Product Form: Paperback
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Many complex systems—from immensely complicated ecosystems to minute assemblages of molecules—surprise us with their simple behavior. Consider, for instance, the snowflake, in which a great number of water molecules arrange themselves in patterns with six-way symmetry. How is it that molecules moving seemingly at random become organized according to the simple, six-fold rule? How do the comings, goings, meetings, and eatings of individual animals add up to the simple dynamics of ecosystem populations? More generally, how does complex and seemingly capricious microbehavior generate stable, predictable macrobehavior?

In this book, Michael Strevens aims to explain how simplicity can coexist with, indeed be caused by, the tangled interconnections between a complex system’s many parts. At the center of Strevens’s explanation is the notion of probability and, more particularly, probabilistic independence. By examining the foundations of statistical reasoning about complex systems such as gases, ecosystems, and certain social systems, Strevens provides an understanding of how simplicity emerges from complexity. Along the way, he draws lessons concerning the low-level explanation of high-level phenomena and the basis for introducing probabilistic concepts into physical theory.

Michael Strevens is Professor of Philosophy at New York University. He received a Guggenheim Fellowship in 2017.

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