04914nam 2200613Ia 450 991077817040332120221108104451.00-674-04406-110.4159/9780674044067(CKB)1000000000786906(StDuBDS)AH23050914(SSID)ssj0000111428(PQKBManifestationID)11133943(PQKBTitleCode)TC0000111428(PQKBWorkID)10074801(PQKB)10155034(Au-PeEL)EBL3300376(CaPaEBR)ebr10318366(OCoLC)923110955(DE-B1597)574586(DE-B1597)9780674044067(MiAaPQ)EBC3300376(OCoLC)1248759270(EXLCZ)99100000000078690620021107d2003 uy 0engur|||||||||||txtccrBigger than chaos[electronic resource] understanding complexity through probability /Michael StrevensCambridge, MA Harvard University Press20031 online resource (xii, 413 p. ) illBibliographic Level Mode of Issuance: Monograph0-674-01042-6 0-674-02259-9 Includes bibliographical references (p. 397-401) and index.Note to the Reader 1. The Simple Behavior of Complex Systems 1.1 Simplicity in Complex Systems 1.2 Enion Probability Analysis 1.3 Towards an Understanding of Enion Probabilities 2. The Physics of Complex Probability 2.1 Complex Probability Quantified 2.2 Microconstant Probability 2.3 The Interpretation of IC-Variable Distributions 2.4 Probabilistic Networks 2.5 Standard IC-Variables 2.6 Complex Probability and Probabilistic Laws 2.7 Effective and Critical IC-Values 2.A The Method of Arbitrary Functions 2.B More on the Tossed Coin 2.C Proofs 3. The Independence of Complex Probabilities 3.1 Stochastic Independence and Selection Rules 3.2 Probabilities of Composite Events 3.3 Causal Independence 3.4 Microconstancy and Independence 3.5 The Probabilistic Patterns Explained 3.6 Causally Coupled Experiments 3.7 Chains of Linked IC-Values 3.A Conditional Probability 3.B Proofs 4. The Simple Behavior of Complex Systems Explained 4.1 Representing Complex Systems 4.2 Enion Probabilities and Their Experiments 4.3 The Structure of Microdynamics 4.4 Microconstancy and Independence of Enion Probabilities 4.5 Independence of Microdynamic Probabilities 4.6 Aggregation of Enion Probabilities 4.7 Grand Conditions for Simple Macrolevel Behavior 4.8 Statistical Physics 4.9 Population Ecology 5. Implications for the Philosophy of the Higher-Level Sciences 5.1 Reduction 5.2 Higher-Level Laws 5.3 Causal Relevance 5.4 The Social Sciences 5.5 The Mathematics of Complex Systems 5.6 Are There Simple Probabilities? Notes Glossary References IndexMichael 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.ProbabilitiesStatistical physicsProbabilities.Statistical physics.003CC 3700rvkStrevens Michael1145008MiAaPQMiAaPQMiAaPQBOOK9910778170403321Bigger than chaos3718345UNINA