Read Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World by Leslie Valiant Free Online
Book Title: Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World|
The author of the book: Leslie Valiant
Format files: PDF
The size of the: 11.42 MB
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Reader ratings: 3.5
Edition: Basic Books
Date of issue: November 14th 2014
ISBN 13: 9780465060726
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From a leading computer scientist, a unifying theory that will revolutionize our understanding of how life evolves and learns.
How does life prosper in a complex and erratic world? While we know that nature follows patterns—such as the law of gravity—our everyday lives are beyond what known science can predict. We nevertheless muddle through even in the absence of theories of how to act. But how do we do it?
In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. The key is “probably approximately correct” algorithms, a concept Valiant developed to explain how effective behavior can be learned. The model shows that pragmatically coping with a problem can provide a satisfactory solution in the absence of any theory of the problem. After all, finding a mate does not require a theory of mating. Valiant’s theory reveals the shared computational nature of evolution and learning, and sheds light on perennial questions such as nature versus nurture and the limits of artificial intelligence.
Offering a powerful and elegant model that encompasses life’s complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence.
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Read information about the authorLeslie Valiant FRS is a British computer scientist and computational theorist. He is currently the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics at Harvard University, and was educated at King's College, Cambridge, Imperial College London, and University of Warwick where he received a PhD in computer science in 1974.
Valiant is world-renowned for his work in theoretical computer science. Among his many contributions to complexity theory, he introduced the notion of #P-completeness to explain why enumeration and reliability problems are intractable. He also introduced the "probably approximately correct" (PAC) model of machine learning that has helped the field of computational learning theory grow, and the concept of holographic algorithms. His earlier work in automata theory includes an algorithm for context-free parsing, which is (as of 2010) still the asymptotically fastest known. He also works in computational neuroscience focusing on understanding memory and learning.
Valiant's 2013 book is Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World (Basic Books, ISBN 9780465032716). In it he argues, among other things, that evolutionary biology does not explain the rate at which evolution occurs, writing, for example, "The evidence for Darwin's general schema for evolution being essentially correct is convincing to the great majority of biologists. This author has been to enough natural history museums to be convinced himself. All this, however, does not mean the current theory of evolution is adequately explanatory. At present the theory of evolution can offer no account of the rate at which evolution progresses to develop complex mechanisms or to maintain them in changing environments."