Hume's Problem Solved: The Optimality of Meta-Induction

Schurz, Gerhard

  • 出版商: Summit Valley Press
  • 出版日期: 2019-05-07
  • 售價: $2,170
  • 貴賓價: 9.5$2,062
  • 語言: 英文
  • 頁數: 400
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 0262039729
  • ISBN-13: 9780262039727
  • 下單後立即進貨 (約3~6週)

商品描述

A new approach to Hume's problem of induction that justifies the optimality of induction at the level of meta-induction.

Hume's problem of justifying induction has been among epistemology's greatest challenges for centuries. In this book, Gerhard Schurz proposes a new approach to Hume's problem. Acknowledging the force of Hume's arguments against the possibility of a noncircular justification of the reliability of induction, Schurz demonstrates instead the possibility of a noncircular justification of the optimality of induction, or, more precisely, of meta-induction (the application of induction to competing prediction models). Drawing on discoveries in computational learning theory, Schurz demonstrates that a regret-based learning strategy, attractivity-weighted meta-induction, is predictively optimal in all possible worlds among all prediction methods accessible to the epistemic agent. Moreover, the a priori justification of meta-induction generates a noncircular a posteriori justification of object induction. Taken together, these two results provide a noncircular solution to Hume's problem.

Schurz discusses the philosophical debate on the problem of induction, addressing all major attempts at a solution to Hume's problem and describing their shortcomings; presents a series of theorems, accompanied by a description of computer simulations illustrating the content of these theorems (with proofs presented in a mathematical appendix); and defends, refines, and applies core insights regarding the optimality of meta-induction, explaining applications in neighboring disciplines including forecasting sciences, cognitive science, social epistemology, and generalized evolution theory. Finally, Schurz generalizes the method of optimality-based justification to a new strategy of justification in epistemology, arguing that optimality justifications can avoid the problems of justificatory circularity and regress.