Author: John R. Koza
Description: Genetic programming may be more powerful than neural networks and other machinelearning techniques, able to solve problems in a wider range of disciplines. In this ground-breakingbook, John Koza shows how this remarkable paradigm works and provides substantial empirical evidencethat solutions to a great variety of problems from many different fields can be found by geneticallybreeding populations of computer programs. Genetic Programming contains a great many worked examplesand includes a sample computer code that will allow readers to run their own programs.In gettingcomputers to solve problems without being explicitly programmed, Koza stresses two points: thatseemingly different problems from a variety of fields can be reformulated as problems of programinduction, and that the recently developed genetic programming paradigm provides a way to search thespace of possible computer programs for a highly fit individual computer program to solve theproblems of program induction. Good programs are found by evolving them in a computer against afitness measure instead of by sitting down and writing them.John R. Koza is Consulting AssociateProfessor in the Computer Science Department at Stanford University.
