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This study extends Modal Empiricism to probabilistic knowledge, offering an inductivist epistemology. Extreme probabilities help test milder ones, advancing understanding of probabilistic reasoning from experience.

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Area of Science:

  • Philosophy of Science
  • Epistemology

Background:

  • Modal Empiricism offers an experiential basis for modal knowledge using possible situations.
  • Current Modal Empiricism lacks a framework for probabilistic knowledge.
  • Inductive approaches to necessity assume representativeness of actual situations.

Purpose of the Study:

  • To extend Modal Empiricism to accommodate probabilistic knowledge.
  • To develop an inductivist epistemology for probabilistic knowledge.
  • To address the limitations of existing theories in explaining probabilistic reasoning.

Main Methods:

  • Replacing possible worlds with coarse-grained, bounded, and relative possible situations.
  • Utilizing extreme probabilities (close to 0 and 1) as proxies.
  • Applying a principle of model combination for testing probabilities.

Main Results:

  • A novel inductivist epistemology for probabilistic knowledge is proposed.
  • The extended framework accounts for probabilistic reasoning from experience.
  • Extreme probabilities are shown to be effective for testing milder probabilities.

Conclusions:

  • Modal Empiricism can be successfully extended to probabilistic knowledge.
  • This provides a robust inductivist framework for understanding probabilistic epistemology.
  • The proposed method offers a new approach to empirical knowledge of probability.