Abstract Our paper introduces an innovative automated system designed to extract logical rules using the $\textbf{T}^{\mathsf{\tiny CL}}$ logic from various datasets, with a particular emphasis on tabular data. Our starting point is the CN2 algorithm. Typically employed for classification tasks, we have adapted this algorithm to suit our descriptive objectives. We consider well-known datasets (such as Iris and Zoo) to illustrate our approach. Furthermore, we extend this analysis to a complex dataset, notably the GTZAN musical dataset. We have then tested our system by reclassifying the songs available in the GTZAN database with respect to the newly generated musical genres, obtaining encouraging results. This example showcases the algorithm’s efficacy in generating descriptive rules across different data domains. We discuss the adaptability of the proposed approach across various data types, including images, sounds and various heterogeneous structures.

We propose a system called METCL (Metaphor Elaboration in Typicality-Based Compositional Logic) able to generate and identify metaphors by using the TCL reasoning framework, specialized in human-like commonsense concept combination. We show that METCL is able to improve both state of-the-art Large Language Models (e.g DeepSeek-R1, GPT-4o, Qwen2.5-Max) and symbolic ones in the task of metaphor identification. Additionally, we show how the metaphors generated by METCL are generally well accepted by human subjects. The obtained results are encouraging and pave the way to research in automatic metaphor generation and comprehension based on the assumption that metaphors interpretation can be partially regarded as a categorization problem relying on generative commonsense concept combination.

Abstract This paper introduces a computational ontology for deontic reasoning, fully implemented in RDF* and SPARQL*, designed to support reasoning in the presence of irresolvable conflicts. These are situations in which two or more norms prescribe incompatible obligations, prohibitions or permissions, without any clear priority among them. Existing approaches in formal deontic logic are typically limited to the propositional level, focused primarily on obligation as the central modality, and are rarely implemented in a way that is compatible with Semantic Web standards. The framework presented here addresses these limitations by providing a first-order, Resource Description Framework (RDF)-based formalization of all standard deontic modalities: obligations, permissions, optionality and their negations. It supports the explicit representation and reasoning about violations and conflicts while also accounting for contextual constraints. The ontology integrates contributions from three research areas that have so far largely developed in isolation: RDF-based LegalTech solutions, reification-based models of Natural Language Semantics and conflict-tolerant approaches in formal deontic logic. By incorporating contradictions and conflicts into the object language, the ontology supports advanced reasoning tasks within a framework that adheres to W3C standards. This makes it suitable for integration into industrial LegalTech applications where normative reasoning is required1.

This article presents an affective-based sensemaking system for grouping and suggesting stories created by the users about the cultural artefacts in a museum. By relying on the TCL commonsense reasoning framework, the system exploits the spatial structure of the Plutchik’s “wheel of emotions” to organize the stories according to their extracted emotions. The process of emotion extraction, reasoning, and suggestion is triggered by an app, called GAMGame, and integrated with the sensemaking engine. Following the framework of Citizen Curation, the system allows classifying and suggesting stories encompassing cultural items able to evoke not only the very same emotions of already experienced or preferred museum objects but also novel items sharing different emotional stances and, therefore, able to break the filter bubble effect and open the users’ view toward more inclusive and empathy-based interpretations of cultural content. The system has been designed tested, in the context of the H2020EU SPICE project (Social cohesion, Participation, and Inclusion through Cultural Engagement), in cooperation with the community of the d/Deaf and on the collection of the Gallery of Modern Art (GAM) in Turin. We describe the user-centered design process of the web app and of its components and we report the results concerning the effectiveness of the diversity-seeking, affective-driven, recommendations of stories.

Abstract In this paper we present our final solution to the problem of designing an efficient theorem prover for Conditional Logics with the selection function semantics. Conditional Logics recently have received a renewed attention and have found several applications in knowledge representation and artificial intelligence. In order to provide an efficient theorem prover for Conditional Logics, we introduce labelled sequent calculi for the logics characterized by well-established axioms systems including the axiom of strong centering CS, the axiom of conditional identity ID, the axiom of conditional modus ponens MP, as well as the conditional third excluded middle CEM, rejected by Lewis but endorsed by Stalnaker, as well as for the whole cube of extensions. The proposed calculi revise and improve the calculi SeqS introduced in Olivetti et al. (2007, ACM Trans. Comput. Logics, 8). We also present an implementation of these calculi in SWI Prolog, including a graphical interface in Python as well as standard heuristics and refinements that allow us to obtain an efficient theorem prover for the logics under consideration. Moreover, we present some statistics about the performances of the theorem prover, which are promising and significantly better than those of its predecessor CondLean, an implementation of the calculi SeqS.

Abstract We present hypersequent calculi for the strongest logics in Lewis’ family of conditional systems, characterized by uniformity and total reflexivity. We first present a non-standard hypersequent calculus, which allows a syntactic proof of cut elimination. We then introduce standard hypersequent calculi, in which sequents are enriched by additional structures to encode plausibility formulas and diamond formulas. Proof search using these calculi is terminating, and the completeness proof shows how a countermodel can be constructed from a branch of a failed proof search. We then describe tuCLEVER, a theorem prover that implements the standard hypersequent calculi. The prover provides a decision procedure for the logics, and it produces a countermodel in case of proof search failure. The prover tuCLEVER is inspired by the methodology of leanTAP and it is implemented in Prolog. Preliminary experimental results show that the performances of tuCLEVER are promising.1

In this work we exploit a recently introduced nonmonotonic extension of Description Logics, able to deal with the problem of knowledge invention via commonsense concept combination, to dynamically generate novel editorial contents in the context of a real broadcasting company: RAI – Radiotelevisione Italiana, the Italian public broadcaster. In particular, we introduce the system implementing such logic, i.e. DENOTER: Dynamic gEnerator of NOvel contents in mulTimEdia bRoadcasting (available online at the URL: http://di.unito.it/denoter), that has been applied and tested in the online multimedia platform of RAI (i.e. RaiPlay) as a tool for both the generation/suggestion of novel genres of multimedia on-demand contents and the reclassification of the available items within such new genres. Our system works by extracting the typical properties characterizing the available genres (with a standard information extraction pipeline) and by building novel classes of genres as the result of a creative combination of such extracted representations. We have tested DENOTER (i) by reclassifying the available contents in RaiPlay with respect to the new generated genres (ii) with an evaluation, in the form of a controlled user study experiment, of the feasibility of using the obtained reclassifications as recommended contents (iii) with a qualitative evaluation done with a small group of experts of RAI. The obtained results are encouraging and pave the way to many possible further improvements and research directions.

We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of the combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC+TR, whose semantics is based on the notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and is equipped with a cognitive heuristic used by humans for concept composition.We first extend the logic of typicality ALC+TR by typicality inclusions of the form p::T(C)⊑D, whose intuitive meaning is that ‘we believe with degree p about the fact that typical Cs are Ds’. As in the distributed semantics, we define different scenarios containing only some typicality inclusions, each one having a suitable probability. We then exploit such scenarios in order to ascribe typical properties to a concept C obtained as the combination of two prototypical concepts. We also show that reasoning in the proposed Description Logic is ExpTime-complete as for the underlying standard Description Logic ALC.

In this work we describe a knowledge based system employed for the dynamic, goal-directed and creative generation of novel knowledge in cognitive agents. This system exploits a recently introduced extension of a Description Logic of typicality (TCL) able to combine prototypical (i.e. commonsense) descriptions of concepts. In particular: given a goal expressed as a set of properties, in case an intelligent agent cannot find a concept in its knowledge base able to fulfill these properties, our system exploits the Description Logic TCL in order to find at least two concepts whose creative combination allows to satisfy the goal. The knowledge base of the agent is then extended via a mechanism of commonsense concept combination where the resulting combined concept represents the solution for the initial goal. The proposed approach has been tested in the task of object composition and compared with the responses provided by the OROC system.

In this work we describe a novel approach to goal-oriented knowledge capturing that, differently from the standard knowledge acquisition pipelines, employs a dynamic conceptual reframing mechanismrelying on a non monotonic reasoning procedure. This approachhas been implemented in a knowledge based system able to findthe solution to not directly satisfiable goals by recombining, in aninnovative way, at least two concepts of a given knowledge base(KB). The output of such combinatorial mechanism results, de facto, in an extension of the initial KB able to satisfy the original goal. The proposed approach has been tested in the task of goal-driven concept invention and has been compared with human responses.

The paper presents a methodology to revise a Description Logic knowledge base when exceptions are detected. The approach exploits concepts and results from techniques developed for debugging Description Logic terminologies. Debugging an inconsistent terminology amounts to identifying a minimal subs et of axioms responsible for the inconsistency (i.e., an error to be removed by a knowledge engineer). Exception handling, instead, requires to revise the axioms causing an inconsistency so that a new consistent knowledge base is obtained, encompassing the detected exception about an individual x. To this aim, we make use of a nonmonotonic extension of the Description Logic 𝒜ℒ𝒞 based on the combination of a typicality operator and the well established nonmonotonic mechanism of rational closure, which allows one to deal with prototypical properties and defeasible inheritance.

This special issue of Fundamenta Informaticae contains the revised, extended versions of selected papers presented at the Italian Conference on Computational Logic (Convegno Italiano di Logica Computazionale, CILC 2014) which was hosted by the University of Turin, Italy, from June 16th to June 18th, 2014.The event was the twenty-ninth edition of the annual meeting of the Italian Association for Logic Programming (GULP, Gruppo Ricercatori e Utenti di Logic Programming).Since its first edition, which took place in Genoa in 1986, the annual conference organized by GULP is the main occasion of meeting and exchanging ideas and experiences among Italian researchers who work in the field of Computational Logic.During the years, this annual meeting extended its horizons from the specific field of traditional Logic Programming to more general declarative programming as well as to Artificial Intelligence and Deductive Databases.All these areas had a very significant growth over the last decades and nowadays they all play a crucial role in the fields of Information Processing and Computer Science.The program of CILC 2014 included 29 technical papers accepted for presentation (23 for long presentation and 6 for short presentation).Paper selection was made by peer reviewing.The technical presentations were of high quality and concerned several topics related to computational logic, including probabilistic logic programming, verification of logic programs, answer set programming, revision and query of ontologies, argumentation theory, proof and decision systems for non-classical logics, computable set theory, multi-agent systems, and machine learning.The conference program included also two invited talks: (i) "From logic programming to argumentation and back", by Francesca Toni (Department of Computing, Imperial College London, U.K.), and (ii) "Tractable approaches to consistent query answering in ontology-based-data access", by Riccardo Rosati (DIAG, Dipartimento di Ingegneria informatica, automatica e gestionale, Università di Roma "Sapienza", Italy).Some of the papers presented at the conference were selected for this special issue and their authors were invited to submit an improved, extended version for publication.The papers that have been accepted went through a two-round careful review by qualified international referees, to whom we express our deep gratitude for their comments and criticisms.

We propose a methodology to revise a Description Logic knowledge base when detecting exceptions. Our approach relies on the methodology for debugging a Description Logic terminology, addressing the problem of diagnosing inconsistent ontologies by identifying a minimal subset of axioms responsible for an inconsistency. In the approach we propose, once the source of the inconsistency has been localized, the identified axioms are revised in order to obtain a consistent knowledge base including the detected exception about an individual x. To this aim, we make use of a nonmonotonic extension of the Description Logic ALC based on the combination of a typicality operator and the well established nonmonotonic mechanism of rational closure, which allows to deal with prototypical properties and defeasible inheritance.

Nested sequent calculi are a useful generalization of ordinary sequent calculi, where sequents are allowed to occur within sequents. Nested sequent calculi have been profitably used in the area of (multi)-modal logic to obtain analytic and modular proof systems for these logics. In this work, we extend the realm of nested sequents by providing nested sequent calculi for the basic conditional logic CK and some of its significant extensions. We provide also a calculus for Kraus Lehman Magidor cumulative logic C. The calculi are internal (a sequent can be directly translated into a formula), cut-free and analytic. Moreover, they can be used to design (sometimes optimal) decision procedures for the respective logics, and to obtain complexity upper bounds. Our calculi are an argument in favour of nested sequent calculi for modal logics and alike, showing their versatility and power.

The paper introduces a framework based on constructive conditional logics to define axiomatization, semantics and proof methods for access control logics. We formalize the well-known says operator as a conditional normal modality and, by considering some specific ombinations of access control axioms, we define four access control logics, namely, CondACLUC⁠, CondACLU4⁠, CondACLIC and CondACLI4⁠. Such logics integrate access control logics with intuitionistic conditional logics and provide a natural formulation of Boolean principals. The well-known 'speaks for' operator introduced in the logic ABLP is defined on the top of the says modality. We provide a Kripke model semantics for the logics and we prove that their axiomatization is sound and complete with respect to the semantics. Also, we develop sound, complete, cut-free sequent calculi for them. For the logic CondACLUC⁠, which (as concerns atomic principals) is slightly stronger than the logic ICL recently introduced by Garg and Abadi, we also provide a terminating sequent calculus, thus proving that the logic is decidable and that validity in CondACLUC is in PSPACE.

We propose a nonmonotonic extension of low complexity Description Logics EL ⊥ and DL-Litecore for reasoning about typicality and defeasible properties. The resulting logics are called EL ⊥ Tmin and DL-LitecTmin. we prove that entailment is in Π p 2 Concerning DL-LitecTmin,. With regard to EL ⊥ Tmin, we first show that entailment remains EXPTIME-hard. Next we consider the known fragment of Left Local EL ⊥ Tmin and we prove that the complexity of entailment drops to Π p 2. 1

We define an Intuitionistic Conditional Logic for Access Control called CICL. The logic CICLis based on a conditional language allowing principals to be defined as arbitrary formulas and it includes few uncontroversial axioms of access control logics. We provide an axiomatization and a Kripke model semantics for the logic CICL, and we prove that the axiomatization is sound and complete with respect to the semantics.

Extensions of Description Logics (DLs) to reason about typicality and defeasible inheritance have been largely investigated. In this paper, we consider two such extensions, namely (i) the extension of DLs with a typicality operator T, having the properties of Preferential nonmonotonic entailment P, and (ii) its variant with a typicality operator having the properties of the stronger Rational entailment R. The first one has been proposed in [6]. Here, we investigate the second one and we show, by a representation theorem, that it is equivalent to the approach to preferential subsumption proposed in [3]. We compare the two extensions, preferential and rational, and argue that the first one is more suitable than the second one to reason about typicality, as the latter leads to very unintuitive inferences.

We extend the Description Logic ALC with a "typicality" operator T that allows us to reason about the prototypical properties and inheritance with exceptions. The resulting logic is called ALC + T. The typicality operator is intended to select the "most normal" or "most typical" instances of a concept. In our framework, knowledge bases may then contain, in addition to ordinary ABoxes and TBoxes, subsumption relations of the form "T(C) is subsumed by P", expressing that typical C-members have the property P. The semantics of a typicality operator is defined by a set of postulates that are strongly related to Kraus-Lehmann-Magidor axioms of preferential logic P. We first show that T enjoys a simple semantics provided by ordinary structures equipped with a preference relation. This allows us to obtain a modal interpretation of the typicality operator. We show that the satisfiability of anALC+Tknowledge base is decidable and it is precisely EXPTIME. We then present a tableau calculus for deciding satisfiability of ALC + T knowledge bases. Our calculus gives a (suboptimal) nondeterministic-exponential time decision procedure for ALC + T. We finally discuss how to extend ALC + T in order to infer defeasible properties of (explicit or implicit) individuals. We propose two alternatives: (i) a nonmonotonic completion of a knowledge base; (ii) a "minimal model" semantics for ALC + T whose intuition is that minimal models are those that maximise typical instances of concepts.

We present tableau calculi for the logics of nonmonotonic reasoning defined by Kraus, Lehmann and Magidor (KLM). We give a tableau proof procedure for all KLM logics, namely preferential, loop-cumulative, cumulative, and rational logics. Our calculi are obtained by introducing suitable modalities to interpret conditional assertions. We provide a decision procedure for the logics considered and we study their complexity.

In this paper we present a cut-free sequent calculus, called SeqS, for some standard conditional logics. The calculus uses labels and transition formulas and can be used to prove decidability and space complexity bounds for the respective logics. We also show that these calculi can be the base for uniform proof systems. Moreover, we present CondLean, a theorem prover in Prolog for these calculi.