DeepAI AI Chat
Log In Sign Up

Transformation-based Feature Computation for Algorithm Portfolios

by   Barry Hurley, et al.
Brown University
University College Cork

Instance-specific algorithm configuration and algorithm portfolios have been shown to offer significant improvements over single algorithm approaches in a variety of application domains. In the SAT and CSP domains algorithm portfolios have consistently dominated the main competitions in these fields for the past five years. For a portfolio approach to be effective there are two crucial conditions that must be met. First, there needs to be a collection of complementary solvers with which to make a portfolio. Second, there must be a collection of problem features that can accurately identify structural differences between instances. This paper focuses on the latter issue: feature representation, because, unlike SAT, not every problem has well-studied features. We employ the well-known SATzilla feature set, but compute alternative sets on different SAT encodings of CSPs. We show that regardless of what encoding is used to convert the instances, adequate structural information is maintained to differentiate between problem instances, and that this can be exploited to make an effective portfolio-based CSP solver.


page 1

page 2

page 3

page 4


Proteus: A Hierarchical Portfolio of Solvers and Transformations

In recent years, portfolio approaches to solving SAT problems and CSPs h...

Simple Algorithm Portfolio for SAT

The importance of algorithm portfolio techniques for SAT has long been n...

Set Constraint Model and Automated Encoding into SAT: Application to the Social Golfer Problem

On the one hand, Constraint Satisfaction Problems allow one to declarati...

SATfeatPy – A Python-based Feature Extraction System for Satisfiability

Feature extraction is a fundamental task in the application of machine l...

Towards a Complexity-theoretic Understanding of Restarts in SAT solvers

Restarts are a widely-used class of techniques integral to the efficienc...

Extreme Algorithm Selection With Dyadic Feature Representation

Algorithm selection (AS) deals with selecting an algorithm from a fixed ...