Applied category theory

Category theory (CT) originated as a subdiscipline of pure mathematics, with a historical strength in unifying disparate mathematical areas to transport proofs and constructions between them. CT can also be viewed as an upgraded foundation for all of math, taking the place traditionally occupied by first-order logic and set theory, and is commonly used in theoretical computer science (especially type theory), and as a foundation for computational theorem-proving. Recent developments have expanded CT’s applicability to areas such as economics, engineering, linguistics, knowledge representation, database theory, and machine learning. We view CT as a high-leverage way to level up research in these areas as well as to facilitate interdisciplinary discourse.

Publications

Dioptics: A common generalization of open games and gradient-based learners

Compositional semantics have been shown for machine-learning algorithms [FST18] and open games [Hed18]; at SYCO 1, remarks were made noting the high degree of overlap in character and analogy between the constructions, and that there is known to be a monoidal embedding from the category of learners to the category of games, but it remained unclear exactly what kind of structure they both are.

Fifth Symposium on Compositional Structures (SYCO) / 2019.09.05 / Birmingham, UK
David Dalrymple
AbstractionLab
Applied category theory

Talks

Dioptics: A common generalization of open games and gradient-based learners

SYCO 5 / 2019.09.06 / Birmingham, UK
David Dalrymple
AbstractionLab
Applied category theory

Blog

AbstractionLab Update: notes from the frontier

The independent researchers of the AbstractionLab tackle ambitious projects with huge potential to drive breakthroughs in computing, communication, and decentralization. They are the scout ship pilots exploring the farthest reaches of the adjacent possible.

Karola Kirsanow
AbstractionLab
Distributed power systems, Knowledge engineering, Applied category theory