Evolutionary Computation: Toward a New Philosophy of Machine Intelligence

Although evolutionary computation has only been a popular topic for the last 20 years, it actually has antecedents back in the '50s. This is the first text to present the most significant and historic papers on evolutionary computation ranging from the '50s to the early '90s. Features a comprehensive bibliography of the available literature in the field.

Computer Science/Artificial Intelligence Evolutionary Computation Toward a New Philosophy of Machine Intelligence Second Edition In this revised and significantly expanded second edition, distinguished scientist David B. Fogel presents the latest advances in both the theory and practice of evolutionary computation to help you keep pace with developments in this fast-changing field. In-depth and updated, Evolutionary Computation shows you how to use simulated evolution to achieve machine intelligence. You will gain current insights into the history of evolutionary computation and the newest theories shaping research. Fogel carefully reviews the "no free lunch theorem" and discusses new theoretical findings that challenge some of the mathematical foundations of simulated evolution. This second edition also presents the latest game-playing techniques that combine evolutionary algorithms with neural networks, including their success in playing competitive checkers. Chapter by chapter, this comprehensive book highlights the relationship between learning and intelligence. Evolutionary Computation features an unparalleled integration of history with state-of-the-art theory and practice for engineers, professors, and graduate students of evolutionary computation and computer science who need to keep up-to-date in this developing field.