Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World
Nature''s Algorithms for Learning and Prospering in a Complex World
A computer scientist presents a theory of the theoryless. The key is "probably approximately correct" learning, Valiant's model of how effective behavior can be learned even in this complex world. Sure to revolutionize the way that the universe's greatest mysteries are examined.
Leslie Valiant is the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics at Harvard University. He is a Fellow of the Royal Society and a member of the National Academy of Sciences. He is a winner of the Nevanlinna Prize from the International Mathematical Union, and the Turing Award, known as the Nobel of computing.
"[A]n engaging meditation on complexity and on how living things often unwittingly use math to navigate it."--"Scientific American" "Computer scientist Leslie Valiant celebrates Alan Turing as the progenitor of a third scientific revolution, potentially as profound as Newton's and Einstein's in transforming our understanding of the world. Why not a 'fourth revolution'--why omit Darwin? Because, Valiant dares to say, Darwin's theory is radically incomplete, and until it is equipped to make quantitative, verifiable predictions, evolution by natural selection cannot account for the complexity of living things and is not 'more than a metaphor.' But Valiant offers no drop of succor to creationists. Rather, he seeks to arm neo-Darwinian theory against their onslaughts by elucidating the mechanistic, quantitative basis it must have in a world 'without a designer.' The algorithms of computational learning theory, he posits, will be key--in particular, a special kind he calls 'ecorithms, ' which incorporate information gathered from the environment to improve an organism's 'performance.' Turing's heirs have only just begun to plot its equation."--"The Scientist" "["Probably Approximately Correct"] really shines as an introduction to computer science theory to the general public, providing a compact and accessible description of basic, important results ... . This is a book that should be on every computer scientist's shelf so that when someone asks, 'Why is computer science theory important?' the three word response can be, 'Read this book.'"--"SIGACT News" "A scholar at the intersection of computing and evolutionary neuroscience, Valiant explores 'ecorithms' algorithms that learn by interacting with their environment, not from their designer--and so are fundamental to the process of evolution. His text is clear and approachable, with some work; the argument is sweeping."--"Harvard Magazine" "This remarkable book is carefully const