Computational epistemology

Computational epistemology is a subdiscipline of formal epistemology that studies the intrinsic complexity of inductive problems for ideal and computationally bounded agents. In short, computational epistemology is to induction what recursion theory is to deduction. It has been applied to problems in philosophy of science.

Themes

Some of the themes of computational epistemology include:

the essential likeness of induction and deduction
the treatment of discovery, prediction and assessment methods as effective procedures as originates in algorithmic learning theory.
the characterization of inductive inference problems as consisting of:

a set of relevant possibilities, each of which specifies some potentially infinite sequence of inputs to scientific method,
a question whose potential answers partition the relevant possibilities,
a convergent success criterion and
a set of admissible methods

the notion of logical reliability for inductive problems

Quotations

Computational epistemology definition:
On making inductive problems easier to solve:
On the divergence of computational epistemology from Bayesian confirmation theory and the like:
Computational epistemology in a nutshell:
On the proper role of methodology: