25 citations · 97 across the 22 of their papers we have counts for
13 papers · 1 filter
Generation and Prediction of Difficult Model Counting Instances
Guillaume Escamocher, Barry O'Sullivan
We present a way to create small yet difficult model counting instances. Our generator is highly parameterizable: the number of variables of the instances it produces, as well as t…
SATfeatPy -- A Python-based Feature Extraction System for Satisfiability
Benjamin Provan-Bessell, Marco Dalla, Andrea Visentin +1
Feature extraction is a fundamental task in the application of machine learning methods to SAT solving. It is used in algorithm selection and configuration for solver portfolios an…
Finding Counterfactual Explanations through Constraint Relaxations
Sharmi Dev Gupta, Begum Genc, Barry O'Sullivan
Interactive constraint systems often suffer from infeasibility (no solution) due to conflicting user constraints. A common approach to recover infeasibility is to eliminate the con…
Solving Logic Grid Puzzles with an Algorithm that Imitates Human Behavior
Guillaume Escamocher, Barry O'Sullivan
We present in this paper our solver for logic grid puzzles. The approach used by our algorithm mimics the way a human would try to solve the same problem. Every progress made durin…
Generating Difficult SAT Instances by Preventing Triangles
Guillaume Escamocher, Barry O'Sullivan, Steven David Prestwich
When creating benchmarks for SAT solvers, we need SAT instances that are easy to build but hard to solve. A recent development in the search for such methods has led to the Balance…
Finding Robust Solutions to Stable Marriage
Begum Genc, Mohamed Siala, Barry O'Sullivan +1
We study the notion of robustness in stable matching problems. We first define robustness by introducing (a,b)-supermatches. An -supermatch is a stable matching in which if…