activity
20172019
collaborators

7 papers

cs.LO2019

Better Paracoherent Answer Sets with Less Resources

Giovanni Amendola, Carmine Dodaro, Francesco Ricca

Answer Set Programming (ASP) is a well-established formalism for logic programming. Problem solving in ASP requires to write an ASP program whose answers sets correspond to solutio…

cs.AI2019

Beyond NP: Quantifying over Answer Sets

Giovanni Amendola, Francesco Ricca, Mirek Truszczynski

Answer Set Programming (ASP) is a logic programming paradigm featuring a purely declarative language with comparatively high modeling capabilities. Indeed, ASP can model problems i…

cs.AI2019

Paracoherent Answer Set Semantics meets Argumentation Frameworks

Giovanni Amendola, Francesco Ricca

In the last years, abstract argumentation has met with great success in AI, since it has served to capture several non-monotonic logics for AI. Relations between argumentation fram…

cs.LO2019

Abstract Solvers for Computing Cautious Consequences of ASP programs

Giovanni Amendola, Carmine Dodaro, Marco Maratea

Abstract solvers are a method to formally analyze algorithms that have been profitably used for describing, comparing and composing solving techniques in various fields such as Pro…

cs.LO2018

New Models for Generating Hard Random Boolean Formulas and Disjunctive Logic Programs

Giovanni Amendola, Francesco Ricca, Miroslaw Truszczynski

We propose two models of random quantified boolean formulas and their natural random disjunctive logic program counterparts. The models extend the standard models of random k-CNF f…

cs.LO2017

On the Computation of Paracoherent Answer Sets

Giovanni Amendola, Carmine Dodaro, Wolfgang Faber +2

Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning. An ASP program can have no answer set due to cyclic default negation. In this case, it is n…