Bigger Than Chaos: Understanding Complexity Through Probability

Εξώφυλλο
Harvard University Press, 30 Ιουν 2003 - 413 σελίδες

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.

 

Περιεχόμενα

The Simple Behavior of Complex Systems
12 Enion Probability Analysis
10
13 Towards an Understanding of Enion Probabilities
25
The Physics of Complex Probability
36
21 Complex Probability Quantified
37
22 Microconstant Probability
45
23 The Interpretation of ICVariable Distributions
68
24 Probabilistic Networks
71
3A Conditional Probability
211
3B Proofs
212
The Simple Behavior of Complex Systems Explained
247
41 Representing Complex Systems
248
42 Enion Probabilities and Their Experiments
249
43 The Structure of Microdynamics
251
44 Microconstancy and Independence of Enion Probabilities
261
45 Independence of Microdynamic Probabilities
273

25 Standard ICVariables
79
26 Complex Probability and Probabilistic Laws
94
27 Effective and Critical ICValues
99
2A The Method of Arbitrary Functions
116
2B More on the Tossed Coin
120
2C Proofs
125
The Independence of Complex Probabilities
137
31 Stochastic Independence and Selection Rules
138
32 Probabilities of Composite Events
139
33 Causal Independence
143
34 Microconstancy and Independence
148
35 The Probabilistic Patterns Explained
159
36 Causally Coupled Experiments
161
37 Chains of Linked ICValues
176
46 Aggregation of Enion Probabilities
284
47 Grand Conditions for Simple Macrolevel Behavior
290
48 Statistical Physics
291
49 Population Ecology
317
Implications for the Philosophy of the HigherLevel Sciences
331
52 HigherLevel Laws
337
53 Causal Relevance
344
54 The Social Sciences
349
55 The Mathematics of Complex Systems
353
Notes
361
Glossary
385
References
395
Index
401
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