Introduction

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book deals with evolutionary biology. It shows the simplest population process model implies the axioms of von Neumann and Morgenstern and a more complex population process model implies the axioms of Savage for a theory of decisionmaking based on subjective probabilities and utilities. The book discusses the theme of Darwinian evolution by asking whether a principle analogous to Darwin's could operate in somatic time. It presents the theme of evolutionary adaptivity, connecting it with ideas derived from thermodynamics and statistical mechanics that led to the proposal for "Boltzmann machines." The book explores more fully, in the context of computer science, the pervasive biological phenomenon of massive parallelism. It describes a neural net model that realizes evolutionary learning and also shows that rabbits, confronted with olfactory stimuli, react to their expectation of an odor rather than solely to the stimulus.