Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World (Hardcover)

Leslie Valiant

  • 出版商: Basic Books
  • 出版日期: 2013-06-04
  • 售價: $1,080
  • 貴賓價: 9.5$1,026
  • 語言: 英文
  • 頁數: 208
  • 裝訂: Hardcover
  • ISBN: 0465032710
  • ISBN-13: 9780465032716
  • 相關分類: Algorithms-data-structures
  • 立即出貨(限量) (庫存=2)


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.




在《可能大致正確》中,計算機科學家萊斯利·瓦利安特(Leslie Valiant)提出了一個精妙的學習和演化綜合理論,展示了個體和集體如何在一個與我們自己一樣複雜的世界中不僅生存,而且繁榮。關鍵在於「可能大致正確」的演算法,這是瓦利安特提出的一個概念,用來解釋如何學習有效的行為。這個模型顯示,在沒有任何問題理論的情況下,實用地應對問題可以提供一個令人滿意的解決方案。畢竟,找到一個伴侶並不需要一個交配理論。瓦利安特的理論揭示了演化和學習的共同計算本質,並闡明了永恆的問題,如天性與養育之爭和人工智能的極限。