This book, written by the foremost international researchers and practitioners of genetic programming (GP), explores the synergy between theoretical and empirical results on realworld problems, producing a comprehensive view of the state of the art in GP. In this year’s edition, the topics covered include many of the most important issues and research questions in the field, such as opportune application domains for GPbased methods, game playing and coevolutionary search, symbolic regression and efficient learning strategies, encodings and representations for GP, schema theorems, and new selection mechanisms. The book includes several chapters on best practices and lessons learned from handson experience. Readers will discover largescale, realworld applications of GP to a variety of problem domains via indepth presentations of the latest and most significant results.
This book, written by the foremost international researchers and practitioners of genetic programming (GP), explores the synergy between theoretical and empirical results on realworld problems, producing a comprehensive view of the state of the art in GP. In this year’s edition, the topics covered include many of the most important issues and research questions in the field, such as opportune application domains for GPbased methods, game playing and coevolutionary search, symbolic regression and efficient learning strategies, encodings and representations for GP, schema theorems, and new selection mechanisms. The book includes several chapters on best practices and lessons learned from handson experience. Readers will discover largescale, realworld applications of GP to a variety of problem domains via indepth presentations of the latest and most significant results.
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