So far as the laws of mathematics refer to reality, they are not certain. And so far as they are certain, they do not refer to reality. -A. Einstein The word "instability" in day-to-day language is associated with some- thing going wrong or being abnormal: exponential growth of cancer cells, irrational behavior of a patient, collapse of a structure, etc. This book, however, is about "good" instabilities, which lead to change, evolution, progress, creativity, and intelligence; they explain the paradox of irreversi- bility in thermodynamics, the phenomena of chaos and turbulence in clas- sical mechanics, and non-deterministic (multi-choice) behavior in biological and social systems. The concept of instability is an attribute of dynamical models that de- scribe change in time of physical parameters, biological or social events, etc. Each dynamical model has a certain sensitivity to small changes or "errors" in initial values of its variables. These errors may grow in time, and if such growth is of an exponential rate, the behavior of the variable is defined as unstable. However, the overall effect of an unstable variable upon the dynamical system is not necessarily destructive. Indeed, there al- ways exists such a group of variables that do not contribute to the energy of the system. In mechanics such variables are called ignorable or cyclic.
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This book deals with predictability and dynamical concepts in biology and physics. The main emphasis is on intrinsic stochasticity caused by the instability of dynamical equations. In particular, the authors present for the first time in book form their concept of terminal dynamics. They demonstrate that instability as an attribute of dynamical models can explain the paradox of irreversibility in thermodynamics, the phenomenon of chaos and turbulence in classical mechanics, and non-deterministic (multi-choice) behavior in biological and social systems. The first part of the book describes the basic properties of instability as an attribute of dynamical models and how their analysis is dependent upon frames of reference. The second part describes these instabilities and their usefullness in physics, biology, neural nets, creativity, intelligence, and social behavior (the "collective brain"). The book addresses researchers as well as students; it should also be of interest to philosophers of science.
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