no code implementations • 17 Feb 2022 • Roberto Amadini, Maurizio Gabbrielli, Tong Liu, Jacopo Mauro
Meta-solver approaches exploits a number of individual solvers to potentially build a better solver.
no code implementations • 11 Mar 2021 • Nicklas Sindlev Andersen, Marco Chiarandini, Jacopo Mauro
To enable the real-time detection of a person with dementia that has lost orientation, we transfer location data at high frequency from a frontend on the smartphone of a person with dementia to a backend system.
Software Engineering
1 code implementation • 7 Sep 2020 • Tong Liu, Roberto Amadini, Jacopo Mauro, Maurizio Gabbrielli
A preliminary version of sunny-as2 was submitted to the Open Algorithm Selection Challenge (OASC) in 2017, where it turned out to be the best approach for the runtime minimization of decision problems.
no code implementations • 28 Jul 2020 • Jacopo Mauro
Feature Models are a mechanism to organize the configuration space and facilitate the construction of software variants by describing configuration options using features, i. e., a name representing a functionality.
no code implementations • 26 Jun 2017 • Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro
In Constraint Programming (CP) a portfolio solver combines a variety of different constraint solvers for solving a given problem.
1 code implementation • 13 Feb 2015 • Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro
*** To appear in IJCAI 2015 proceedings *** In Constraint Programming (CP), a portfolio solver uses a variety of different solvers for solving a given Constraint Satisfaction / Optimization Problem.
no code implementations • 14 Nov 2013 • Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro
In this paper we present SUNNY: a simple and flexible algorithm that takes advantage of a portfolio of constraint solvers in order to compute --- without learning an explicit model --- a schedule of them for solving a given Constraint Satisfaction Problem (CSP).
no code implementations • 1 Aug 2013 • Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro
Recent research has shown that a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers.
no code implementations • 4 Dec 2012 • Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro
Recent research in areas such as SAT solving and Integer Linear Programming has shown that the performances of a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers.