Bigger than chaos :: understanding complexity through probability /
Michael Strevens shows how simplicity can co-exist with the tangled interconnections within complex systems. By looking at the foundations of statistical reasoning about complex systems (gases, ecosystems and even social systems) he provides an understanding of how simplicity emerges from complexity...
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1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cambridge, Massachusetts :
Harvard University Press,
[2003]
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Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | Michael Strevens shows how simplicity can co-exist with the tangled interconnections within complex systems. By looking at the foundations of statistical reasoning about complex systems (gases, ecosystems and even social systems) he provides an understanding of how simplicity emerges from complexity. 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. |
Beschreibung: | 1 online resource (xii, 413 pages :) |
Bibliographie: | Includes bibliographical references (pages 397-401) and index. |
ISBN: | 9780674044067 0674044061 0674022599 9780674022591 9780674010420 0674010426 |
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520 | |a Michael Strevens shows how simplicity can co-exist with the tangled interconnections within complex systems. By looking at the foundations of statistical reasoning about complex systems (gases, ecosystems and even social systems) he provides an understanding of how simplicity emerges from complexity. | ||
520 | |a 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. | ||
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author | Strevens, Michael |
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discipline | Informatik Philosophie |
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illustrated | Illustrated |
indexdate | 2024-10-25T16:17:10Z |
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publisher | Harvard University Press, |
record_format | marc |
spelling | Strevens, Michael, author. http://id.loc.gov/authorities/names/n2002011598 Bigger than chaos : understanding complexity through probability / Michael Strevens. Cambridge, Massachusetts : Harvard University Press, [2003] 1 online resource (xii, 413 pages :) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file rdaft Includes bibliographical references (pages 397-401) and index. Print version record. Michael Strevens shows how simplicity can co-exist with the tangled interconnections within complex systems. By looking at the foundations of statistical reasoning about complex systems (gases, ecosystems and even social systems) he provides an understanding of how simplicity emerges from complexity. 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. English. Probabilities. http://id.loc.gov/authorities/subjects/sh85107090 Probability https://id.nlm.nih.gov/mesh/D011336 Probabilités. probability. aat SCIENCE System Theory. bisacsh TECHNOLOGY & ENGINEERING Operations Research. bisacsh SCIENCE Chaotic Behavior in Systems. bisacsh Probabilities fast Complexe structuren. gtt Waarschijnlijkheid (statistiek) gtt has work: Bigger than chaos (Text) https://id.oclc.org/worldcat/entity/E39PCH6GT3xM836tRrKFddyKh3 https://id.oclc.org/worldcat/ontology/hasWork Print version: Strevens, Michael. Bigger than chaos. Cambridge, Mass. : Harvard University Press, 2003 0674010426 (DLC) 2002192237 (OCoLC)51088130 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=282318 Volltext CBO01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=282318 Volltext |
spellingShingle | Strevens, Michael Bigger than chaos : understanding complexity through probability / Probabilities. http://id.loc.gov/authorities/subjects/sh85107090 Probability https://id.nlm.nih.gov/mesh/D011336 Probabilités. probability. aat SCIENCE System Theory. bisacsh TECHNOLOGY & ENGINEERING Operations Research. bisacsh SCIENCE Chaotic Behavior in Systems. bisacsh Probabilities fast Complexe structuren. gtt Waarschijnlijkheid (statistiek) gtt |
subject_GND | http://id.loc.gov/authorities/subjects/sh85107090 https://id.nlm.nih.gov/mesh/D011336 |
title | Bigger than chaos : understanding complexity through probability / |
title_auth | Bigger than chaos : understanding complexity through probability / |
title_exact_search | Bigger than chaos : understanding complexity through probability / |
title_full | Bigger than chaos : understanding complexity through probability / Michael Strevens. |
title_fullStr | Bigger than chaos : understanding complexity through probability / Michael Strevens. |
title_full_unstemmed | Bigger than chaos : understanding complexity through probability / Michael Strevens. |
title_short | Bigger than chaos : |
title_sort | bigger than chaos understanding complexity through probability |
title_sub | understanding complexity through probability / |
topic | Probabilities. http://id.loc.gov/authorities/subjects/sh85107090 Probability https://id.nlm.nih.gov/mesh/D011336 Probabilités. probability. aat SCIENCE System Theory. bisacsh TECHNOLOGY & ENGINEERING Operations Research. bisacsh SCIENCE Chaotic Behavior in Systems. bisacsh Probabilities fast Complexe structuren. gtt Waarschijnlijkheid (statistiek) gtt |
topic_facet | Probabilities. Probability Probabilités. probability. SCIENCE System Theory. TECHNOLOGY & ENGINEERING Operations Research. SCIENCE Chaotic Behavior in Systems. Probabilities Complexe structuren. Waarschijnlijkheid (statistiek) |
url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=282318 |
work_keys_str_mv | AT strevensmichael biggerthanchaosunderstandingcomplexitythroughprobability |