Evolving solutions to community-structured satisfiability formulas

Frank Neumann, Andrew M. Sutton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We study the ability of a simple mutation-only evolutionary algorithm to solve propositional satisfiability formulas with inherent community structure. We show that the community structure translates to good fitness-distance correlation properties, which implies that the objective function provides a strong signal in the search space for evolutionary algorithms to locate a satisfying assignment efficiently. We prove that when the formula clusters into communities of size s ? ?(log n) n O(ne/(2e+2)) for some constant 0 < e < 1, and there is a nonuniform distribution over communities, a simple evolutionary algorithm called the (1+1) EA finds a satisfying assignment in polynomial time on a 1 - o(1) fraction of formulas with at least constant constraint density. This is a significant improvement over recent results on uniform random formulas, on which the same algorithm has only been proven to be efficient on uniform formulas of at least logarithmic density.

Original languageEnglish (US)
Title of host publication33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
PublisherAAAI press
Pages2346-2353
Number of pages8
ISBN (Electronic)9781577358091
StatePublished - 2019
Event33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 - Honolulu, United States
Duration: Jan 27 2019Feb 1 2019

Publication series

Name33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019

Conference

Conference33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
CountryUnited States
CityHonolulu
Period1/27/192/1/19

Fingerprint Dive into the research topics of 'Evolving solutions to community-structured satisfiability formulas'. Together they form a unique fingerprint.

Cite this