Description: In the long term, the best hope for fast productive software development may lie within the field of genetic programming -- the application of machine learning techniques to computer programs themselves. The goal of GP is to create computer programs that can evolve in response to their data environment, generating new code to handle new tasks as needed. This book presents the first comprehensive tutorial introduction to this emerging field, placing GP within the context of machine-learning, biology, and classical computer science. Beginning with basic evolutionary computation concepts, the authors proceed to discuss the training and improvement of genetic programs, implementation and optimization issues, and real world applications. Anyone researching or simply interested in the automatic evolution of computer programs will benefit from this informative overview.

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