Exploring the landscape of the space of heuristics for local search in SAT

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{burnett:2017:CEC,

• author = "Andrew W. Burnett and Andrew J. Parkes",
• booktitle = "2017 IEEE Congress on Evolutionary Computation (CEC)",
• title = "Exploring the landscape of the space of heuristics for local search in SAT",
• year = "2017",
• editor = "Jose A. Lozano",
• pages = "2518--2525",
• address = "Donostia, San Sebastian, Spain",
• publisher = "IEEE",
• isbn13 = "978-1-5090-4601-0",
• abstract = "Local search is a powerful technique on many combinatorial optimisation problems. However, the effectiveness of local search methods will often depend strongly on the details of the heuristics used within them. There are many potential heuristics, and so finding good ones is in itself a challenging search problem. A natural method to search for effective heuristics is to represent the heuristic as a small program and then apply evolutionary methods, such as genetic programming. However, the search within the space of heuristics is not well understood, and in particular little is known of the associated search landscapes. In this paper, we consider the domain of propositional satisfiability (SAT), and a generic class of local search methods called `WalkSAT'. We give a language for generating the heuristics; using this we generated over three million heuristics, in a systematic manner, and evaluated their associated fitness values. We then use this data set as the basis for an initial analysis of the landscape of the space of heuristics. We give evidence that the heuristic landscape exhibits clustering. We also consider local search on the space of heuristics and show that it can perform quite well, and could complement genetic programming methods on that space.",
• keywords = "genetic algorithms, genetic programming, computability, search problems, WalkSAT, clustering, combinatorial optimisation problems, evolutionary methods, local search, propositional satisfiability, search space landscapes, Computer science, Measurement, Reactive power, Systematics",
• isbn13 = "978-1-5090-4601-0",
• DOI = "doi:10.1109/CEC.2017.7969611",
• month = "5-8 " # jun,
• notes = "IEEE Catalog Number: CFP17ICE-ART Also known as \cite{7969611}",

}

Genetic Programming entries for Andrew W Burnett Andrew J Parkes

Citations