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.
