π€ AI Summary
This study investigates the computational complexity of constraint satisfaction problems (CSPs) over finite domains, aiming to precisely delineate the boundary between polynomial-time solvable and NP-hard cases. By adopting graph homomorphism as a unifying framework, the work systematically employs universal algebraic methods, with particular emphasis on the algebraic underpinnings of cyclic term operations and the bounded-width theorem. The project establishes a solvability criterion for CSPs based on algebraic invariants, which not only clarifies the theoretical foundations of existing complexity classifications but also provides an effective tool for identifying new tractable classes. This advances a deeper understanding of the fine-grained structure of the complexity landscape for finite-domain CSPs.
π Abstract
Constraint satisfaction problems are computational problems that naturally appear in many areas of theoretical computer science. One of the central themes is their computational complexity, and in particular the border between polynomial-time tractability and NP-hardness. In this course we introduce the universal-algebraic approach to study the computational complexity of finite-domain CSPs. The course covers in particular the cyclic terms and bounded width theorems. To keep the presentation accessible, we start the course in the tangible setting of directed graphs and graph homomorphism problems.