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156The paper presents the heterogeneous proxytypes hypothesis as a cognitively-inspired computational framework able to reconcile, in both natural and artificial systems, different theories of typicality about conceptual representation and reasoning that have been traditionally seen as incompatible. In particular, through the Dual PECCS system and its evolution, it shows how prototypes, exemplars and theory-theory like conceptual representations can be integrated in a cognitive artificial agent (th…Read more
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172Cognitive Heuristics for Commonsense Thinking and Reasoning in the next generation Artificial IntelligenceSRM ACM Student Chapters. 2021.Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this talk, we discuss the different paradigms that have been developed in AI and Computational Cognitive Science to deal with this problem (ranging from logic-based methods, to diagrammatic-based ones). In particular, we discuss - via two different case studies concerning commonsense …Read more
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158Cognitive Agents with CommonsenseI-Cog Talks. 2021.Commonsense reasoning is a crucial human ability employed in everyday tasks. In this talk I provide a knowledge level analysis of the main representational and reasoning problems affecting the cognitive architectures for what concerns this issue. In providing this analysis I will show, by considering some of the main cognitive architectures currently available (e.g. SOAR, ACT-R, CLARION), how one of the main problems of such architectures is represented by the fact that their knowledge represent…Read more
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1013Book: Cognitive Design for Artificial MindsRoutledge, Taylor & Francis Ltd. 2021.Book Description (Blurb): Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. Beginning with an overview of the historical, met…Read more
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162Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this talk, I will show how commonsense reasoning plays a crucial role in this respect. In particular, I will present a cognitively inspired reasoning framework for knowledge invention and creative problem solving exploiting TCL: a non-monotonic extension of a Description Logic (DL) of typicality able to combine prototypical (commonsense) descriptions of concepts i…Read more
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316What cognitive research can do for AI: a case studyIn AI*IA, Springer. pp. 1-8. 2020.This paper presents a practical case study showing how, despite the nowadays limited collaboration between AI and Cognitive Science (CogSci), cognitive research can still have an important role in the development of novel AI technologies. After a brief historical introduction about the reasons of the divorce between AI and CogSci research agendas (happened in the mid’80s of the last century), we try to provide evidence of a renewed collaboration by showing a recent case study on a commonsen…Read more
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183Dynamic conceptual reframing represents a crucial mechanism employed by humans, and partially by other animal species, to generate novel knowledge used to solve complex goals. In this talk, I will present a reasoning framework for knowledge invention and creative problem solving exploiting TCL: a non-monotonic extension of a Description Logic (DL) of typicality able to combine prototypical (commonsense) descriptions of concepts in a human-like fashion [1]. The proposed approach has been tested…Read more
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377Beyond subgoaling: A dynamic knowledge generation framework for creative problem solving in cognitive architecturesCognitive Systems Research 58 305-316. 2019.In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent…Read more
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285On the Impact of Fallacy-based Schemata and Framing Techniques in Persuasive TechnologiesCognititar Workshop @ECAI 2020. 2020.Persuasive technologies can adopt several strategies to change the attitudes and behaviors of their users. In this work we present some empirical results stemming from the hypothesis - firstly formulated in [3] - that there is a strong connection between some well known cognitive biases reducible to fallacious argumentative schemata and some of the most common persuasion strategies adopted within digital technologies. In particular, we will report how both framing and fallacious-reducible mechan…Read more
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271La modellizzazione computazionale della competenza inferen-ziale e della competenza referenzialeSistemi Intelligenti. forthcoming.In philosophy of language, a distinction has been proposed by Diego Marconi between two aspects of lexical competence, i.e. referential and inferential competence. The former accounts for the relation-ship of words to the world, the latter for the relationship of words among themselves. The aim of the pa-per is to offer a critical discussion of the kind of formalisms and computational techniques that can be used in Artificial Intelligence to model the two aspects of lexical competence, and of th…Read more
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227A Non Monotonic Reasoning framework for Goal-Oriented Knowledge AdaptationIn Paglieri (ed.), Proceedings of AISC 2019, Università Degli Studi Di Roma Tre. pp. 12-14. 2019.In this paper we present a framework for the dynamic and automatic generation of novel knowledge obtained through a process of commonsense reasoning based on typicality-based concept combination. We exploit a recently introduced extension of a Description Logic of typicality able to combine prototypical descriptions of concepts in order to generate new prototypical concepts and deal with problem like the PET FISH (Osherson and Smith, 1981; Lieto & Pozzato, 2019). Intuitively, in the context of o…Read more
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343Spazi multidimensionali per la rappresentazione semanticaPenguin-Random House. 2019.Nel campo delle scienze cognitive molti oggi condividono l’ipotesi che siano necessari differenti tipi di rappresentazioni per modellare i sistemi cognitivi sia naturali, sia artificiali. Si considerino le rappresentazioni basate su reti neurali, i formalismi simbolici e rappresentazioni analogiche quali rappresentazioni diagrammatiche o modelli mentali. Tutti questi metodi hanno successo nello spiegare e modellare alcune classi di fenomeni cognitivi, ma nessuno è in grado di rendere conto di tu…Read more
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403A Description Logic Framework for Commonsense Conceptual Combination Integrating Typicality, Probabilities and Cognitive HeuristicsJournal of Experimental and Theoretical Artificial Intelligence 1-39. 2019.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 th…Read more
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131Bounded Rationality and Heuristics in Humans and in Artificial Cognitive SystemsIsonomía. Revista de Teoría y Filosofía Del Derecho 1 (4): 1-21. 2019.In this paper I will present an analysis of the impact that the notion of “bounded rationality”, introduced by Herbert Simon in his book “Administrative Behavior”, produced in the field of Artificial Intelligence (AI). In particular, by focusing on the field of Automated Decision Making (ADM), I will show how the introduction of the cognitive dimension into the study of choice of a rational (natural) agent, indirectly determined - in the AI field - the development of a line of research aiming at…Read more
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539Il Ruolo delle Scienze Cognitive nell’Intelligenza Artificiale del FuturoIn Proceedings of Ital-IA. pp. 240-242. 2019.Questo contributo si propone di fornire uno spunto di riflessione, e una breve panoramica storica, sul ruolo che le scienze cognitive hanno giocato, e possono ancora giocare, nello sviluppo dei sistemi intelligenti di nuova generazione. Illustra, inoltre, le attività recenti che l’AISC (Associazione Italiana di Scienze Cognitive, di cui gli autori sono attualmente Vice-Presidente e Presidente) sta portando avanti per lo sviluppo di linee di ricerca nell’ambito dei sistemi artificiali di inspiraz…Read more
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237In questo contributo descriviamo un sistema di creatività computazionale in grado di generare automaticamente nuovi concetti utilizzando una logica descrittiva non monotòna che integra tre ingredienti principali: una logica descrittiva della tipicalità, una estensione probabilistica basata sulla semantica distribuita nota come DISPONTE, e una euristica di ispirazione cognitiva per la combinazione di più concetti. Una delle applicazioni principali del sistema riguarda il campo della creatività co…Read more
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599Mappe concettuali vs ontologie. Un confronto sull'utilizzo di strumenti informatici per la didatticaIn Cristiano Chesi (ed.), Atti dell'Associazione Italiana di Scienze Cogntitive. pp. 4-7. 2019.Questo lavoro propone un confronto tra diversi strumenti utilizzabili per modellare la conoscenza di dominio in ambito didattico: le mappa concettuali, Novak e Cañas (2006), (uno strumento tradizionalmente utilizzato nelle scuole) e le ontologie computazionali (dei sistemi formali di modellazione concettuale, attualmente molto usati nei sistemi di intelligenza artificiale per le loro capacità di “ragionamento automatico”, si veda Guarino, (1995)). Nello specifico, questo articolo presenta il ris…Read more
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538Computational Models (of Narrative) for Literary StudiesSemicerchio, Rivista di Poesia Comparata 2 (LIII): 38-44. 2015.In the last decades a growing body of literature in Artificial Intelligence (AI) and Cognitive Science (CS) has approached the problem of narrative understanding by means of computational systems. Narrative, in fact, is an ubiquitous element in our everyday activity and the ability to generate and understand stories, and their structures, is a crucial cue of our intelligence. However, despite the fact that - from an historical standpoint - narrative (and narrative structures) have been an import…Read more
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217Non classical concept representation and reasoning in formal ontologiesDissertation, Università degli Studi di Salerno. 2012.Formal ontologies are nowadays widely considered a standard tool for knowledge representation and reasoning in the Semantic Web. In this context, they are expected to play an important role in helping automated processes to access information. Namely: they are expected to provide a formal structure able to explicate the relationships between different concepts/terms, thus allowing intelligent agents to interpret, correctly, the semantics of the web resources improving the performances of the sea…Read more
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218AISC 2018 - Extended Abstract Pavia - December 2018In Cristiano Chesi (ed.), AISC Proceedings, Pavia.. pp. 20-23. forthcoming.Extended abstract presented at the AISC 2018 Conference, 15th International Conference of the Italian Association of Cognitive Science, Pavia.
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7AISC 18 Proceedings, Extended Abstract: The computational modeling of lexical competenceIn Jacques Fleuriot, Dongming Wang & Jacques Calmet (eds.), Artificial Intelligence and Symbolic Computation: 13th International Conference, AISC 2018, Suzhou, China, September 16–19, 2018, Proceedings, Springer. pp. 20-22. 2018.In philosophy of language, a distinction has been proposed between two aspects of lexical competence, i.e. referential and inferential competence (Marconi 1997). The former accounts for the relationship of words to the world, the latter for the relationship of words among themselves. The distinction may simply be a classification of patterns of behaviour involved in ordinary use of the lexicon. Recent research in neuropsychology and neuroscience, however, suggests that the distinction might be n…Read more
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1144Ontologies, Mental Disorders and PrototypesIn Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence, Springer Verlag. pp. 189-204. 2019.As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field do not allow for the representation of concepts in terms of typical traits. However, the need of representin…Read more
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288The computational modeling of inferential and referential competenceIn Fabrizio Calzavarini & Antonio Lieto (eds.), AISC 2018 Proceedings. 2018.Abstract.
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248Composing Prototypes - AISC 18In Antonio Lieto & Gian Luca Pozzato (eds.), Proceedings of AISC 2018, 15th Annual Conference of the Italian Association for Cognitive Sciences The new era of Artificial Intelligence: a cognitive perspective, . pp. 8-10. 2018.Combining typical knowledge to generate novel concepts is an important creative trait of human cognition. Dealing with such ability requires, from an AI perspective, the harmonization of two conflicting requirements that are hardly accommodated in symbolic systems: the need of a syntactic compositionality (typical of logical systems) and that one concerning the exhibition of typicality effects (see Frixione and Lieto, 2012). In this work we provide a logical framework able to account for this ty…Read more
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340Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful…Read more
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466Higher-level Knowledge, Rational and Social Levels Constraints of the Common Model of the MindProcedia Computer Science. forthcoming.In his famous 1982 paper, Allen Newell [22, 23] introduced the notion of knowledge level to indicate a level of analysis, and prediction, of the rational behavior of a cognitive articial agent. This analysis concerns the investigation about the availability of the agent knowledge, in order to pursue its own goals, and is based on the so-called Rationality Principle (an assumption according to which "an agent will use the knowledge it has of its environment to achieve its goals" [22, p. 17]. By u…Read more
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611A Description Logic of Typicality for Conceptual CombinationIn Antonio Lieto & Gian Luca Pozzato (eds.), Proceedings of ISMIS 18, Springer. 2018.We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of combining prototypical concepts, an open problem in the fields of AI and cognitive modelling. Our logic extends the logic of typicality ALC + TR, based on the notion of rational closure, by inclusions p :: T(C) v D (“we have probability p that typical Cs are Ds”), coming from the distributed semantics of probabilistic Description Logics. Additionally, it embeds a set of cognitive heuristics for concep…Read more
Università degli Studi di Salerno
PhD, 2012
Turin, Piedmont, Italy
Areas of Specialization
Epistemology |
Philosophy of Mind |
Logic and Philosophy of Logic |
Philosophy of Cognitive Science |