Alberto Paparella

Alberto Paparella

he/him

PhD fellow in Mathematics interested in Logic and Computer Science

Talks and presentations

Introducing a general framework for many-valued temporal and spatial logic.

November 06, 2025

Conference talk, Australasian Association for Logic Conference 2024, University of Queensland, Brisbane, Queensland, Australia

We aim to introduce a possible many-valued extension for well-known temporal and spatial logics based on the family of finite FLew-algebras, allowing for a unified treatment of both fuzzy logics and Heyting algebras, leveraging the notion of a many-valued linear order and allowing for the definition of a many-valued semantics of modal frames. This framework is also implemented as part of an open-source framework for representing, reasoning, and learning from structured and unstructured data, namely Sole.jl, serving as the foundation for reasoning and learning tools leveraging many-valued temporal and spatial logics.

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Symbolic Learning and Rule Extraction with Sole.jl

October 02, 2025

Conference talk, JuliaCon Local Paris 2025, Paris, France

In this presentation, we will have a look at how Sole.jl works through a hands-on tutorial, emphatizing on its comprehensiveness and user-friendliness. This will also allow us to introduce two newcomers to the SOLE ecosystem: ModalAssociationRules.jl, a package for mining association rules between instances, and SolePostHoc.jl, a package to extract, interpret and simplify sets of rules starting from a symbolic model.

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Vector space embeddings of modal logic formulas: theory and application

August 04, 2025

Poster session, 36th European Summer School in Logic, Language and Information, Ruhr University Bochum

Reasoning tasks over modal logics are notoriously difficult, comprising problems which are often semi-decidable. Hence, it is not rare for applications leveraging such tasks to exploit heuristic approaches able to give results in an acceptable amount of time, at the cost of some inaccuracies. Some approaches may benefit from vector embeddings, allowing for instance to involve neural networks and machine learning models in the reasoning process. This work aims at providing a new way to provide such embeddings specifically for the modal case, allowing for faster reasoning through both mathematical and learning techniques.

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Modal FLew-Algebra Satisfiability Through First-Order Translation

July 21, 2025

Conference talk, Logic, Algebra, and Truth Degrees (LATD 2025), University of Siena, Siena, Italy

In this work, we provide an accessible and open-source algorithmic tool for (i) defining finite FLew-algebras, (ii) writing formulas in a specified FLew-algebra, and (iii) asking alpha-satisfiability and alpha-validity for a given value alpha in the algebra of the formula through a first-order translation and making use of a sat or a smt solver, such as z3.

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Many-Expert Decision Trees

October 22, 2024

Workshop talk, Brisbane Logic Workshop, University of Queensland, Brisbane, Queensland, Australia

Taking inspiration from the literature fuzzy decision trees, and leveraging many-valued logics, we propose a novel, and more general variety of decision trees.

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