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Fading Foundations : Probability and the Regress Problem.

Bibliographic Details
Main Author: Atkinson, David.
Other Authors: Peijnenburg, Jeanne.
Format: eBook
Language:English
Published: Cham : Springer International Publishing AG, 2017.
Edition:1st ed.
Series:Synthese Library
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Preface
  • Contents
  • Chapter 1: The Regress Problem
  • Abstract
  • 1.1 Reasons for Reasons: Agrippa's Trilemma
  • 1.2 Coherentism and Infinitism
  • 1.3 Vicious Versus Innocuous Regress
  • Chapter 2: Epistemic Justification
  • Abstract
  • 2.1 Making a Concept Clear
  • 2.2 Two Questions
  • 2.3 Entailment
  • 2.4 Probabilistic Support
  • 2.5 Smith's Normic Support
  • 2.6 Alston's Epistemic Probability
  • Chapter 3: The Probabilistic Regress
  • Abstract
  • 3.1 A New Twist
  • 3.2 The Lewis-Reichenbach Dispute
  • 3.3 Lewis's Argument
  • 3.4 A Counterexample
  • 3.5 A Nonuniform Probabilistic Regress
  • 3.6 Usual and Exceptional Classes
  • 3.7 Barbara Bacterium
  • Chapter 4: Fading Foundations and the Emergence of Justification
  • Abstract
  • 4.1 Fading Foundations
  • 4.2 Propositions versus Beliefs
  • 4.3 Emergence of Justification
  • 4.4 Where Does the Justification Come From?
  • 4.5 Tour d'horizon
  • Chapter 5: Finite Minds
  • Abstract
  • 5.1 Ought-Implies-Can
  • 5.2 Completion and Computation
  • 5.3 Probabilistic Justification as a Trade-Off
  • 5.4 Carl the Calculator
  • Chapter 6: Conceptual Objections
  • Abstract
  • 6.1 The No Starting Point Objection
  • 6.2 A Probabilistic Regress Needs No Starting Point
  • 6.3 The Reductio Argument
  • 6.4 How the Probabilistic Regress Avoids the Reductio
  • 6.5 Threshold and Closure Constraints
  • 6.6 Symmetry and Nontransitivity
  • Chapter 7: Higher-Order Probabilities
  • Abstract
  • 7.1 Two Probabilistic Regresses
  • 7.2 Second- and Higher-Order Probabilities
  • 7.3 Rescher's Argument
  • 7.4 The Two Regresses Are Isomorphic
  • 7.5 Making Coins
  • Chapter 8: Loops and Networks
  • Abstract
  • 8.1 Tortoises and Serpents
  • 8.2 One-Dimensional Loops
  • 8.3 Multi-Dimensional Networks
  • 8.4 The Mandelbrot Fractal
  • 8.5 Mushrooming Out
  • 8.6 Causal Graphs
  • Appendix A: The Rule of Total Probability.
  • A.1 Iterating the rule of total probability
  • A.2 Extrema of the finite series
  • A.3 Convergence of the infinite series
  • A.4 When does the remainder term vanish?
  • A.5 Example in the usual class
  • A.6 Example in the exceptional class
  • A.7 The regress of entailment
  • A.8 Markov condition and conjunctions
  • Appendix B: Closure Under Conjunction
  • Appendix C: Washing Out of the Prior
  • C.1 Washing out
  • C.2 Example: a bent coin
  • C.3 Washing out is not fading away
  • Appendix D: Fixed-Point Methods
  • D.1 Linear iteration
  • D.2 Quadratic Iteration
  • References
  • Index.

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