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Genetic Programming IV: Routine Human-Competitive Machine Intelligence

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Since using evolutionary algorithms for my work, it is easy to see how many of the current EAs can be used to solve or tackle various real world problems. But what Koza does once again is to argue the case that GP is more than just an optimization algorithm but instead an algorithm that tries to show what AI should do and how user and AI should interact to solve a problem. Once again numerous examples are given, with detail on how problems are laid out so as to get the best results from the GP. Koza shows that with well thought out planning GP's can be applied to all sorts of fields.
In one of the chapters he presents the characteristics a problem should have for GP to be applicable.
All-round Great work, my advice get all his books and digest how he approaches various problems with GP. This example format Koza uses is far more useful than talking about what GP is and its theory. Though for a good intro into Evolutionary Algorithms including GP get either Foundations of Genetic Programming or an Introduction to Genetic Programming. An all round good intro is Introduction to Evolutionary Computing.