IJCAI 2020poster0 citations

Lower Bounds and Faster Algorithms for Equality Constraints

Peter Jonsson, Victor Lagerkvist

Abstract

We study the fine-grained complexity of NP-complete, infinite-domain constraint satisfaction problems (CSPs) parameterised by a set of first-order definable relations (with equality). Such CSPs are of central importance since they form a subclass of any infinite-domain CSP parameterised by a set of first-order definable relations. We prove that under the randomised exponential-time hypothesis it is not possible to find c > 1 such that a CSP over an arbitrary finite equality language is solvable in O(c^n) time (n is the number of variables). Stronger lower bounds are possible for infinite equality languages where we rule out the existence of 2^o(n log n) time algorithms; a lower bound which also extends to satisfiability modulo theories solving for an arbitrary background theory. Despite these lower bounds we prove that for each c > 1 there exists an NP-hard equality CSP solvable in O(c^n) time. Lower bounds like these immediately ask for closely matching upper bounds, and we prove that a CSP over a finite equality language is always solvable in O(c^n) time for a fixed c.

Knowledge Representation and Reasoning: Computational Complexity of ReasoningConstraints and SAT: Constraint SatisfactionConstraints and SAT: Satisfiability Modulo Theories
BibTeX
@inproceedings{ijcai2020p247,
  title     = {Lower Bounds and Faster Algorithms for Equality Constraints},
  author    = {Jonsson, Peter and Lagerkvist, Victor},
  booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
               Artificial Intelligence, {IJCAI-20}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Christian Bessiere},
  pages     = {1784--1790},
  year      = {2020},
  month     = {7},
  note      = {Main track},
  doi       = {10.24963/ijcai.2020/247},
  url       = {https://doi.org/10.24963/ijcai.2020/247},
}