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Related papers: Categorical Complexity

200 papers

The concept of complexity appears in virtually all areas of knowledge. Its intuitive meaning shares similarities across fields, but disagreements between its details hinders a general definition, leading to a plethora of proposed…

Statistical Mechanics · Physics 2023-10-04 Roberto C. Alamino

Restriction categories provide a categorical framework for partiality. In this paper, we introduce three new categorical theories for partiality: local categories, partial categories, and inclusion categories. The objects of a local…

Category Theory · Mathematics 2025-12-04 Marcello Lanfranchi , Jean-Simon Pacaud Lemay

This paper proposes a formal cognitive framework for problem solving based on category theory. We introduce cognitive categories, which are categories with exactly one morphism between any two objects. Objects in these categories are…

Artificial Intelligence · Computer Science 2017-09-15 Francisco J. Arjonilla , Tetsuya Ogata

We introduce a construction that turns a category of pure state spaces and operators into a category of observable algebras and superoperators. For example, it turns the category of finite-dimensional Hilbert spaces into the category of…

Quantum Physics · Physics 2014-09-17 Bob Coecke , Chris Heunen , Aleks Kissinger

The aim of these notes is to provide a succinct, accessible introduction to some of the basic ideas of category theory and categorical logic. The notes are based on a lecture course given at Oxford over the past few years. They contain…

Category Theory · Mathematics 2015-05-27 Samson Abramsky , Nikos Tzevelekos

The term {\em complexity} is used informally both as a quality and as a quantity. As a quality, complexity has something to do with our ability to understand a system or object -- we understand simple systems, but not complex ones. On…

Adaptation and Self-Organizing Systems · Physics 2009-11-19 Russell K. Standish

This article is a short introduction to generic case complexity, which is a recently developed way of measuring the difficulty of a computational problem while ignoring atypical behavior on a small set of inputs. Generic case complexity…

Computational Complexity · Computer Science 2007-07-11 Robert Gilman , Alexei G. Miasnikov , Alexey D. Myasnikov , Alexander Ushakov

We extend the definitions of complexity measures of functions to domains such as the symmetric group. The complexity measures we consider include degree, approximate degree, decision tree complexity, sensitivity, block sensitivity, and a…

Computational Complexity · Computer Science 2020-10-16 Neta Dafni , Yuval Filmus , Noam Lifshitz , Nathan Lindzey , Marc Vinyals

Partiality is a natural phenomenon in computability that we cannot get around. So, the question is whether we can give the areas where partiality occurs, that is, where non-termination happens, more structure. In this paper we consider…

Logic in Computer Science · Computer Science 2023-11-13 Dieter Spreen

We explore a definition of complexity based on logic functions, which are widely used as compact descriptions of rules in diverse fields of contemporary science. Detailed numerical analysis shows that (i) logic complexity is effective in…

Data Analysis, Statistics and Probability · Physics 2016-03-11 Marco Gherardi , Pietro Rotondo

Given a reference computer, Kolmogorov complexity is a well defined function on all binary strings. In the standard approach, however, only the asymptotic properties of such functions are considered because they do not depend on the…

Machine Learning · Computer Science 2007-05-23 Andrei N. Soklakov

The simplification of a multigraph into a simple graph can be abstracted to a more general comma category under some common conditions. When using the identity functor, the category of simple objects in a comma category generalizes the…

Combinatorics · Mathematics 2024-02-20 Will Grilliette

For a nice-enough category $\mathcal{C}$, we construct both the morphism category ${\rm H}(\mathcal{C})$ of $\mathcal{C}$ and the category ${\rm mod}\mbox{-}\mathcal{C}$ of all finitely presented contravariant additive functors over…

Representation Theory · Mathematics 2023-08-01 Rasool Hafezi , Hossein Eshraghi

A new approach is suggested to characterize algebraically automorphisms of the category of free algebras of a given variety. It gives in many cases an answer to the problem set by the first of authors, if automorphisms of such a category…

Category Theory · Mathematics 2007-05-23 Boris Plotkin , Grigori Zhitomirski

The study of abstraction and composition - the focus of category theory - naturally leads to sophisticated diagrams which can encode complex algebraic semantics. Consequently, these diagrams facilitate a clearer visual comprehension of…

Category Theory · Mathematics 2024-06-27 Vincent Abbott , Gioele Zardini

A concept of "evolving categories" is suggested to build a simple, scalable, mathematically consistent framework for representing in uniform way both data and algorithms. A state machine for executing algorithms becomes clear, rich and…

Data Structures and Algorithms · Computer Science 2007-05-23 Evgeny Yanenko

The paper proposes a vector generalization of the basic concepts of the theory of complex variable: the concept of modulus and argument of complex number. The author introduces some generalizations of the notion of holomorphic functions and…

Complex Variables · Mathematics 2011-05-16 A. K. Bakhtin

For any class of operators which transform unary total functions in the set of natural numbers into functions of the same kind, we define what it means for a real function to be uniformly computable or conditionally computable with respect…

Logic · Mathematics 2013-10-23 Ivan Georgiev , Dimiter Skordev

We present a categorical construction for modelling causal structures within a general class of process theories that include the theory of classical probabilistic processes as well as quantum theory. Unlike prior constructions within…

Quantum Physics · Physics 2023-06-22 Aleks Kissinger , Sander Uijlen

Many learning algorithms have invariances: when their training data is transformed in certain ways, the function they learn transforms in a predictable manner. Here we formalize this notion using concepts from the mathematical field of…

Machine Learning · Computer Science 2019-05-07 Kenneth D. Harris