Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 69 tok/s
Gemini 2.5 Pro 52 tok/s Pro
GPT-5 Medium 37 tok/s Pro
GPT-5 High 28 tok/s Pro
GPT-4o 119 tok/s Pro
Kimi K2 218 tok/s Pro
GPT OSS 120B 456 tok/s Pro
Claude Sonnet 4.5 33 tok/s Pro
2000 character limit reached

A categorical perspective on constraint satisfaction: The wonderland of adjunctions (2503.10353v1)

Published 13 Mar 2025 in cs.LO and math.CT

Abstract: The so-called algebraic approach to the constraint satisfaction problem (CSP) has been a prevalent method of the study of complexity of these problems since early 2000's. The core of this approach is the notion of polymorphisms which determine the complexity of the problem (up to log-space reductions). In the past few years, a new, more general version of the CSP emerged, the promise constraint satisfaction problem (PCSP), and the notion of polymorphisms and most of the core theses of the algebraic approach were generalised to the promise setting. Nevertheless, recent work also suggests that insights from other fields are immensely useful in the study of PCSPs including algebraic topology. In this paper, we provide an entry point for category-theorists into the study of complexity of CSPs and PCSPs. We show that many standard CSP notions have clear and well-known categorical counterparts. For example, the algebraic structure of polymorphisms can be described as a set-functor defined as a right Kan extension. We provide purely categorical proofs of core results of the algebraic approach including a proof that the complexity only depends on the polymorphisms. Our new proofs are substantially shorter and, from the categorical perspective, cleaner than previous proofs of the same results. Moreover, as expected, are applicable more widely. We believe that, in particular in the case of PCSPs, category theory brings insights that can help solve some of the current challenges of the field.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube