12 found
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  1.  59
    DOLCE: A Descriptive Ontology for Linguistic and Cognitive Engineering.Stefano Borgo, Roberta Ferrario, Aldo Gangemi, Nicola Guarino, Claudio Masolo, Daniele Porello, Sanfilippo Emilio & Laure Vieu - 2022 - Applied ontology 1 (17):45-69.
    DOLCE, the first top-level (foundational) ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. dolce is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. dolce clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, (...)
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  2.  20
    Pink Panthers and Toothless Tigers: Three Problems in Classification.Guendalina Righetti, Daniele Porello, Oliver Kutz, Nicolas Troquard & Claudio Masolo - 2019 - In Proceedings of the 7th International Workshop on Artificial Intelligence and Cognition, Manchester, UK, September 10-11, 2019. {CEUR} Workshop Proceedings 2483. pp. 39-53.
    Many aspects of how humans form and combine concepts are notoriously difficult to capture formally. In this paper, we focus on the representation of three particular such aspects, namely overexten- sion, underextension, and dominance. Inspired in part by the work of Hampton, we consider concepts as given through a prototype view, and by considering the interdependencies between the attributes that define a concept. To approach this formally, we employ a recently introduced family of operators that enrich Description Logic languages. These (...)
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  3. The Interplay Between Models and Observations.Claudio Masolo, Alessander Botti Benevides & Daniele Porello - 2018 - Applied ontology 13 (1):41-71.
    We propose a formal framework to examine the relationship between models and observations. To make our analysis precise,models are reduced to first-order theories that represent both terminological knowledge – e.g., the laws that are supposed to regulate the domain under analysis and that allow for explanations, predictions, and simulations – and assertional knowledge – e.g., information about specific entities in the domain of interest. Observations are introduced into the domain of quantification of a distinct first-order theory that describes their nature (...)
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  4. Understanding Predication in Conceptual Spaces.Daniele Porello & Claudio Masolo - 2016 - In Roberta Ferrario & Werner Kuhn (eds.), Formal Ontology in Information Systems. Proceedings of the Ninth International Conference (FOIS 2016). pp. 139--152.
    We argue that a cognitive semantics has to take into account the possibly partial information that a cognitive agent has of the world. After discussing Gärdenfors's view of objects in conceptual spaces, we offer a number of viable treatments of partiality of information and we formalize them by means of alternative predicative logics. Our analysis shows that understanding the nature of simple predicative sentences is crucial for a cognitive semantics.
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  5.  98
    A Toothful of Concepts: Towards a Theory of Weighted Concept Combination.Daniele Porello, Oliver Kutz, Guendalina Righetti, Nicolas Troquard, Pietro Galliani & Claudio Masolo - 2019 - In Mantas Simkus & Grant E. Weddell (eds.), Proceedings of the 32nd International Workshop on Description Logics, Oslo, Norway, June 18-21, 2019.
    We introduce a family of operators to combine Description Logic concepts. They aim to characterise complex concepts that apply to instances that satisfy \enough" of the concept descriptions given. For instance, an individual might not have any tusks, but still be considered an elephant. To formalise the meaning of "enough", the operators take a list of weighted concepts as arguments, and a certain threshold to be met. We commence a study of the formal properties of these operators, and study some (...)
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  6. A Cognitive View of Relevant Implication.Daniele Porello & Claudio Masolo - 2015 - In Antonio Lieto, Cristina Battaglino, Daniele P. Radicioni & Manuela Sanguinietti (eds.), Proceedings of the 3rd International Workshop on Artificial Intelligence and Cognition, Turin, Italy, September 28-29, 2015. pp. 40--53.
    Relevant logics provide an alternative to classical implication that is capable of accounting for the relationship between the antecedent and the consequence of a valid implication. Relevant implication is usually explained in terms of information required to assess a proposition. By doing so, relevant implication introduces a number of cognitively relevant aspects in the de nition of logical operators. In this paper, we aim to take a closer look at the cognitive feature of relevant implication. For this purpose, we develop (...)
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  7. Organisations and Variable Embodiments.Daniele Porello, Roberta Ferrario & Claudio Masolo - 2018 - In Stefano Borgo, Pascal Hitzler & Oliver Kutz (eds.), Formal Ontology in Information Systems - Proceedings of the 10th International Conference, {FOIS} 2018, Cape Town, South Africa, 19-21 September 2018. pp. 127--140.
    How can organisations survive not only the substitution of members, but also other dramatic changes, like that of the norms regulating their activities, the goals they plan to achieve, or the system of roles that compose them? This paper is as first step towards a well-founded ontological analysis of the persistence of organisations through changes. Our analysis leverages Kit Fine’s notions of rigid and variable embodiment and proposes to view the (history of the) decisions made by the members of the (...)
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  8.  18
    Design Knowledge Representation: An Ontological Perspective.Emilio M. Sanfilippo, Claudio Masolo & Daniele Porello - 2015 - In Proceedings of the 1st Workshop on Artificial Intelligence and Design, {A} workshop of the {XIV} International Conference of the Italian Association for Artificial Intelligence (AI*IA 2015), Ferrara, Italy, September 22, 2015. pp. 41-54.
    We present a preliminary high-level formal theory, grounded on knowledge representation techniques and foundational ontologies, for the uniform and integrated representation of the different kinds of (quali- tative and quantitative) knowledge involved in the designing process. We discuss the conceptual nature of engineering design by individuating and analyzing the involved notions. These notions are then formally charac- terized by extending the DOLCE foundational ontology. Our ultimate purpose is twofold: (i) to contribute to foundational issues of design; and (ii) to support (...)
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  9.  22
    Concept Combination in Weighted Logic.Guendalina Righetti, Claudio Masolo, Nicolas Toquard, Oliver Kutz & Daniele Porello - 2021 - In Proceedings of the Joint Ontology Workshops 2021 Episode {VII:} The Bolzano Summer of Knowledge co-located with the 12th International Conference on Formal Ontology in Information Systems {(FOIS} 2021), and the 12th Internati.
    We present an algorithm for concept combination inspired and informed by the research in cognitive and experimental psychology. Dealing with concept combination requires, from a symbolic AI perspective, to cope with competitive needs: the need for compositionality and the need to account for typicality effects. Building on our previous work on weighted logic, the proposed algorithm can be seen as a step towards the management of both these needs. More precisely, following a proposal of Hampton [1], it combines two weighted (...)
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  10.  17
    Pluralities, Collectives, and Composites.Claudio Masolo, Laure Vieu, Stefano Borgo, Roberta Ferrario & Daniele Porello - 2020 - In Boyan Brodaric & Fabian Neuhaus (eds.), Formal Ontology in Information Systems - Proceedings of the 11th International Conference, {FOIS} 2020, Cancelled / Bozen-Bolzano, Italy, September 14-17, 2020. Frontiers in Artificial Intelligence and Applications 330. pp. 186-200.
    Forests, cars and orchestras are very different ontological entities, and yet very similar in some aspects. The relationships they have with the elements they are composed of is often assumed to be reducible to standard ontological relations, like parthood and constitution, but how this could be done is still debated. This paper sheds light on the issue starting from a linguistic and philosophical analysis aimed at understanding notions like plurality, collective and composite, and propos- ing a formal approach to characterise (...)
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  11.  17
    Features and Components in Product Models.Emilio M. Sanfilippo, Claudio Masolo, Stefano Borgo & Daniele Porello - 2016 - In Formal Ontology in Information Systems - Proceedings of the 9th International Conference, {FOIS} 2016, Annecy, France, July 6-9, 2016. Frontiers in Artificial Intelligence and Applications 283. pp. 227-240.
    Product structures are represented in engineering models by depicting and linking components, features and assemblies. Their understanding requires knowledge of both design and manufacturing practices, and yet further contextual reasoning is needed to read them correctly. Since these representations are essen- tial to the engineering activities, the lack of a clear and explicit semantics of these models hampers the use of information systems for their assessment and exploita- tion. We study this problem by identifying different interpretations of structure rep- resentations, (...)
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  12.  77
    Representing Concepts by Weighted Formulas.Daniele Porello & Claudio Masolo - 2018 - In Stefano Borgo, Pascal Hitzler & Oliver Kutz (eds.), Formal Ontology in Information Systems - Proceedings of the 10th International Conference, {FOIS} 2018, Cape Town, South Africa, 19-21 September 2018. IOS Press. pp. 55--68.
    A concept is traditionally defined via the necessary and sufficient conditions that clearly determine its extension. By contrast, cognitive views of concepts intend to account for empirical data that show that categorisation under a concept presents typicality effects and a certain degree of indeterminacy. We propose a formal language to compactly represent concepts by leveraging on weighted logical formulas. In this way, we can model the possible synergies among the qualities that are relevant for categorising an object under a concept. (...)
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