• Publications
  • Influence
How the growth of science ends theory change
  • L. Fahrbach
  • Philosophy, Computer Science
  • Synthese
  • 1 May 2011
TLDR
A defense of scientific realism against the pessimistic meta-induction which appeals to the phenomenon of the exponential growth of science. Expand
  • 55
  • 3
  • PDF
Theory Change and Degrees of Success
  • L. Fahrbach
  • Mathematics
  • Philosophy of Science
  • 1 December 2011
Scientific realism is the position that success of a scientific theory licenses an inference to its approximate truth. The argument from pessimistic metainduction maintains that this inference isExpand
  • 28
Understanding Brute Facts
  • L. Fahrbach
  • Philosophy, Computer Science
  • Synthese
  • 1 July 2005
Brute facts are facts that have no explanation. If we come to know that a fact is brute, we obviously don’t get an explanation of that fact. Nevertheless, we do make some sort of epistemic gain. InExpand
  • 11
Scientific revolutions and the explosion of scientific evidence
  • L. Fahrbach
  • Philosophy, Computer Science
  • Synthese
  • 1 December 2017
TLDR
We defend scientific realism against the pessimistic induction by restricting realism to theories whose empirical success matches (or betters) the empirical success enjoyed by our current best theories. Expand
  • 9
  • PDF
PESSIMISTIC META-INDUCTION AND THE EXPONENTIAL GROWTH OF SCIENCE
In my talk, I aim to defend scientific realism against the pessimistic meta-induction (PI, for short). Scientific realism, as I define it, endorses the success-to-truth principle, i.e., the principleExpand
  • 7
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Book Review
LUDWIG FAHRBACH UNDERSTANDING BRUTE FACTS
Brute facts are facts that have no explanation. If we come to know that a fact is brute, we obviously don’t get an explanation of that fact. Nevertheless, we do make some sort of epistemic gain. InExpand
Disuniformity Principle, Pessimistic Induction, Scientific Realism, Uniformity Principle
The pessimistic induction is built upon the uniformity principle that the future resembles the past. In daily scientific activities, however, scientists sometimes rely on what I call theExpand
Introduction: novel predictions.
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