John H. Holland

In this Very Short Introduction, John Holland presents an introduction to the science of complexity. Using examples from biology and economics, he shows how complexity science models the behaviour of complex systems.

A Very Short Introduction

Complexity

How Adaptation Builds Complexity (Helix Books)

Hidden Order

In this important book, John H. Holland dramatically shows us that the “emergence” of order from disorder has much to teach us about life, mind and organizations. Creative activities in both the arts and the sciences depend upon an ability to model the world. The most creative of those models exhibits emergent properties, so that “what comes out is more than what goes in.” From the ingenious checkers-playing computer that started beating its creator in game after game, to the emotive creations of the poet, Emergence shows that Holland's theory successfully predicts many complex behaviors in art and science.

From Chaos To Order

Emergence

An overarching framework for comparing and steering complex adaptive systems is developed through understanding the mechanisms that generate their intricate signal/boundary hierarchies.

Building Blocks for Complex Adaptive Systems

Signals and Boundaries

Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications. In its most familiar form, adaptation is a biological process, whereby organisms evolve by rearranging genetic material to survive in environments confronting them. In this now classic work, Holland presents a mathematical model that allows for the nonlinearity of such complex interactions. He demonstrates the model's universality by applying it to economics, physiological psychology, game theory, and artificial intelligence and then outlines the way in which this approach modifies the traditional views of mathematical genetics. Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways. Along the way he accounts for major effects of coadaptation and coevolution: the emergence of building blocks, or schemata, that are recombined and passed on to succeeding generations to provide, innovations and improvements.

An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence

Adaptation in Natural and Artificial Systems

Richard E. Nisbett

Keith J. Holyoak

Paul R. Thagard

Two psychologists, a computer scientist, and a philosopher have collaborated to present a framework for understanding processes of inductive reasoning and learning in organisms and machines. Theirs is the first major effort to bring the ideas of several disciplines to bear on a subject that has been a topic of investigation since the time of Socrates. The result is an integrated account that treats problem solving and induction in terms of rule�based mental models. Induction is included in the Computational Models of Cognition and Perception Series. A Bradford Book.

John H. Holland

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