Probably Approximately Correct: Nature’s Algorithms for Learning and Prospering in a Complex World

Turing Award–winning computer scientist and Harvard professor Valiant introduces readers to “ecorithms,” his term for formalized trial-and-error approaches to problem solving that provide valuable insight into everything from evolution to artificial intelligence. His concept—a portmanteau of “eco-” and “algorithm”—is modeled on the coping mechanisms and adaptations life forms use to survive and thrive. By codifying these processes to be applicable to any environment, Valiant says, researchers can create a “probably approximately correct” (PAC) model for learning that links Darwin’s theory of evolution with problems at the heart of computer science. He grounds his hypotheses in solid computational theory, drawing on Alan Turing’s pioneering work on “robust” problem-solving and algorithm design, and in successive chapters he demonstrates how ecorithms can depict evolution as a search for optimized performance, as well as help computer scientists create machine intelligence. While Valiant’s basic idea may seem obvious to many readers, his book offers a broad look at how ecorithms may be applied successfully to a variety of challenging problems. 17 b&w figures & glossary. (June)