The aim of this paper is to explore the limits of this heuristic approach to Inference to the Best Explanation and argue for a particular heuristic conception of IBE that respects these limits

2017

The aim of this paper is to explore the limits of this heuristic approach to Inference to the Best Explanation and argue for a particular heuristic conception of IBE that respects these limits

2017

- Much of the recent literature on Inference to the Best Explanation concerns how, if at all, IBE fits into a Bayesian approach to non-deductive reasoning
- The aim of this paper is to explore the limits of this heuristic approach to IBE and argue for a particular heuristic conception of IBE that respects these limits
- Just as heuristic conceptions of IBE generally do not aim to replace standard Bayesian epistemology, but rather to supplement the it by providing an accessible decision procedure to approximate Bayesian reasoning, my suggestion here is that comparative probabilities may provide an accessible heuristic to approximate standard Bayesian decision theory in the special case in which we are choosing between competing explanatory hypotheses
- I have argued, that there are limitations in principle to how much can be asked of IBE in this respect, since explanatory considerations are not typically suitable for indicating the absolute probability values with which Bayesianism is standardly seen as operating
- In light of these limitations, I have argued that IBE is best construed as a heuristic for estimating which hypotheses have the highest probability among those explanatory hypotheses that are available at a given time
- Inference to the Best Explanation complements Bayesianism by providing a heuristic for deciding how to structure subsequent inquiry in a given domain so as to maximize the