The language and constructions of category theory have proven useful in unifying disparate fields of study and bridging formal gaps between approaches, so it is natural that a categorial eye should be turned to the theory of probability and its relation to formal logic. Continuing from the foundational work of Lawvere and Giry in developing a functorial theory of probability, Stuartz and Culbertson detail the central importance of and connection between deterministic processes and stochastic processes. Fong expanded this theory to give a categorical account of Bayesian causality. Here we collect and summarize the rich body of research in categorical probability theory, and further develop mathematical machinery for applications in algorithmic Bayesian statistics.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Girardo, David Orion

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-011414-170605

Advisor

• Servatius, Brigitte

Year

• 2014

Date created

• 2014-01-14

Resource type

• Major Qualifying Project

Major

• Mathematical Sciences

Rights statement

• In Copyright