Marcello Frixione

In the present paper, we shall discuss the notion of prototype and show its benefits. First, we shall argue that the prototypes of common-sense concepts are necessary for making prompt and reliable categorisations and inferences. However, the features constituting the prototype of a particular concept are neither necessary nor sufficient conditions for determining category membership; in this sense, the prototype might lead to conclusions regarded as wrong from a theoretical perspective. That being said, the prototype remains essential to handling most ordinary situations and helps us to perform important cognitive tasks. To exemplify this point, we shall focus on disease concepts. Our analysis concludes that the prototypical conception of disease is needed to make important inferences from a practical and clinical point of view. Moreover, it can still be compatible with a classical definition of disease, given in terms of necessary and sufficient conditions. In the first section, we shall compare the notion of stereotype, as it has been introduced in philosophy of language by Hilary Putnam, with the notion of prototype, as it has been developed in the cognitive sciences. In the second section, we shall discuss the general role of prototypical information in cognition and stress its centrality. In the third section, we shall apply our previous discussion to the specific case of medical concepts, before briefly summarising our conclusions in section four.

During the last decades, many cognitive architectures (CAs) have been realized adopting different assumptions about the organization and the representation of their knowledge level. Some of them (e.g. SOAR [35]) adopt a classical symbolic approach, some (e.g. LEABRA[ 48]) are based on a purely connectionist model, while others (e.g. CLARION [59]) adopt a hybrid approach combining connectionist and symbolic representational levels. Additionally, some attempts (e.g. biSOAR) trying to extend the representational capacities of CAs by integrating diagrammatical representations and reasoning are also available [34]. In this paper we propose a reflection on the role that Conceptual Spaces, a framework developed by Peter G¨ardenfors [24] more than fifteen years ago, can play in the current development of the Knowledge Level in Cognitive Systems and Architectures. In particular, we claim that Conceptual Spaces offer a lingua franca that allows to unify and generalize many aspects of the symbolic, sub-symbolic and diagrammatic approaches (by overcoming some of their typical problems) and to integrate them on a common ground. In doing so we extend and detail some of the arguments explored by G¨ardenfors [23] for defending the need of a conceptual, intermediate, representation level between the symbolic and the sub-symbolic one. In particular we focus on the advantages offered by Conceptual Spaces (w.r.t. symbolic and sub-symbolic approaches) in dealing with the problem of compositionality of representations based on typicality traits. Additionally, we argue that Conceptual Spaces could offer a unifying framework for interpreting many kinds of diagrammatic and analogical representations. As a consequence, their adoption could also favor the integration of diagrammatical representation and reasoning in CAs.

Come è emerso dall’analisi filosofica e dalla ricerca nelle scienze cogni- tive, la maggior parte dei concetti, tra cui molti concetti medici, esibisce degli “effetti prototipici” e non riesce ad essere definita nei termini di condizioni necessarie e sufficienti. Questo aspetto rappresenta un problema per la pro- gettazione di ontologie in informatica, poiché i formalismi adottati per la rap- presentazione della conoscenza (a partire da OWL – Web Ontology Langua- ge) non sono in grado di rendere conto dei concetti nei termini dei loro tratti prototipici. Nel presente articolo ci concentriamo sulla classe dei disordini mentali facendo riferimento alle descrizioni che ne vengono date nel DSM-5. L’idea è quella di proporre un approccio ibrido, in cui i formalismi delle ontologie sono combinati a una rappresentazione geometrica della conoscenza basata sugli spazi concettuali.

Concept representation is still an open problem in the field of ontology engineering and, more generally, of knowledge representation. In particular, the issue of representing “non classical” concepts, i.e. concepts that cannot be defined in terms of necessary and sufficient conditions, remains unresolved. In this paper we review empirical evidence from cognitive psychology, according to which concept representation is not a unitary phenomenon. On this basis, we sketch some proposals for concept representation, taking into account suggestions from psychological research. In particular, it seems that human beings employ both prototype-based and exemplar-based representations in order to represent non classical concepts. We suggest that a similar, hybrid prototype-exemplar based approach could also prove useful in the field of knowledge representation technology. Finally, we propose conceptual spaces as a suitable framework for developing some aspects of this proposal.

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 (such as, in the first place, the Web Ontology Language - OWL) do not allow for the representation of concepts in terms of typical traits. The need of representing concepts in terms of typical traits concerns almost every domain of real world knowledge, including medical domains. In particular, in this article we take into account the domain of mental disorders, starting from the DSM-5 descriptions of some specific disorders. We favour a hybrid approach to concept representation, in which ontology oriented formalisms are combined to a geometric representation of knowledge based on conceptual space. As a preliminary step to apply our proposal to mental disorder concepts, we started to develop an OWL ontology of the schizophrenia spectrum, which is as close as possible to the DSM-5 descriptions.

In this paper, we discuss the conceptual structure of cocktail recipes. This topic involves engaging questions for philosophers and food theorists due to some peculiar characteristics of cocktail recipes, such as the fact that they are standardised by international associations but, nonetheless, vagueness in some elements of the recipes introduces a degree of variability between cocktails of the same type. Our proposal is that a classical theory of concepts is unable to account for such peculiar features. Thus, only a hybrid theoretical approach, combining definitional and prototypical aspects, can capture how cocktail recipes are usually conceptualised among bartenders and mixologists: while the spirit is usually a necessary (though not sufficient) condition for establishing whether an individual cocktail falls under a specific cocktail concept, all the other ingredients and procedures listed in recipes may vary to a certain extent. In order to assess whether variability in prototypical elements of cocktail recipes has any limitations, we exploit the notion of conceptual scheme applied to cocktail recipes and argue that, as long as the quality dimensions of a specific cocktail are respected, its identity remains unchanged regardless of changes in the ingredients or in its preparation.

The problem of concept representation is relevant for many sub-fields of cognitive research, including psychology and philosophy, as well as artificial intelligence. In particular, in recent years it has received a great deal of attention within the field of knowledge representation, due to its relevance for both knowledge engineering as well as ontology-based technologies. However, the notion of a concept itself turns out to be highly disputed and problematic. In our opinion, one of the causes of this state of affairs is that the notion of a concept is, to some extent, heterogeneous, and encompasses different cognitive phenomena. This results in a strain between conflicting requirements, such as compositionality, on the one hand and the need to represent prototypical information on the other. In some ways artificial intelligence research shows traces of this situation. In this paper, we propose an analysis of this current state of affairs. Since it is our opinion that a mature methodology with which to approach knowledge representation and knowledge engineering should also take advantage of the empirical results of cognitive psychology concerning human abilities, we outline some proposals for concept representation in formal ontologies, which take into account suggestions from psychological research. Our basic assumption is that knowledge representation systems whose design takes into account evidence from experimental psychology may therefore give better results in many applications

Pour la plupart des systèmes de représentation de la connaissance orientés concept, l’un des problèmes principaux relève de la commodité technique. A savoir, la représentation de connaissance en termes prototypiques, tout comme la possibilité d’exploiter des formes de raisonnement conceptuel basées sur la typicalité, ne sont pas autorisées. Au contraire, dans les sciences cognitives, il existe des données en faveur de concepts prototypiques, et des formes non-monotoniques de raisonnement conceptuel ont été largement étudiées. Ce fossé cognitif concernant la représentation et le raisonnement constitue un problème pour les systèmes computationnels, puisque l’information prototypique joue un rôle crucial dans plusieurs tâches importantes. Dans la lignée des théories du raisonnement et de la rationalité dites du double processus, nous soutenons que la représentation conceptuelle dans les systèmes computationnels devrait dépendre de (au moins) deux composantes représentationnelles, chacune spécialisée dans le traitement de différents genres de processus de raisonnement. Dans cet article, nous présentons les avantages computationnels de cette approche en termes de double processus, et les comparons brièvement avec d’autres solutions d’orientation logique, adoptées pour traiter du même problème.

Wines with geographical indication can be classified and represented by such features as designations of origin, producers, vintage years, alcoholic strength, and grape varieties; these features allow us to define wines in terms of a set of necessary and/or sufficient conditions. However, wines can also be identified by other characteristics, involving their look, smell, and taste; in this case, it is hard to define wines in terms of necessary and/or sufficient conditions, as wine concepts exhibit typicality effects. This is a setback for the design of computer science ontologies aiming to represent wine concepts, since knowledge representation formalisms commonly adopted in this field do not allow for the representation of concepts in terms of typical traits. To solve this problem, we propose to adopt a hybrid approach in which ontology-oriented formalisms are combined with a geometric representation of knowledge based on conceptual spaces. As in conceptual spaces, concepts are identified in terms of a number of quality dimensions. In order to determine those relevant for wine representation, we use the terminology developed by the Italian Association of Sommeliers to describe wines. This will allow us to understand typicality effects about wines, determine prototypes and better exemplars, and measure the degree of similarity between different wines.

In recent years, a trend in AI research has started to pursue human-level, general artificial intelli-gence (AGI). Although the AGI framework is characterised by different viewpoints on what intelligence is and how to implement it in artificial systems, it conceptualises intelligence as flexible, general-purposed, and capable of self-adapting to different contexts and tasks. Two important ques-tions remain open: a) should AGI projects simu-late the biological, neural, and cognitive mecha-nisms realising the human intelligent behaviour? and b) what is the relationship, if any, between the concept of general intelligence adopted by AGI and that adopted by psychometricians, i.e., the g factor? In this paper, we address these ques-tions and invite researchers in AI to open a dis-cussion on the theoretical conceptions and practi-cal purposes of the AGI approach.

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 tutti gli aspetti della cognizione. A partire da queste considerazioni, riteniamo che sistemi intelligenti e architetture cognitive possano trarre vantaggio dalla combinazione di sistemi di rappresentazione diversi. Si pone allora il problema di fare interagire rappresentazioni di natura differente in maniera cognitivamente e teoricamente fondata. La nostra ipotesi è che gli spazi concettuali possano offrire una sorta di lingua comune, che consentirebbe di integrare e generalizzare molti aspetti delle impostazioni sopra menzionate, superando i limiti delle varie proposte intese singolarmente.

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 representing concepts in terms of typical traits concerns almost every domain of real world knowledge, including medical domains. In particular, in this article we take into account the domain of mental disorders, starting from the DSM-5 descriptions of some specific mental disorders. On this respect, we favor a hybrid approach to the representation of psychiatric concepts, in which ontology oriented formalisms are combined to a geometric representation of knowledge based on conceptual spaces.

During the last decades it has emerged that concepts probably do not constitute a homogeneous set of entities from a psychological point of view. Various divides can be drawn between different types of concepts. Probably, the main empirical achievement in this field has been the inadequacy of the so-called “classical view”: most concepts cannot be characterised in terms of sets of necessary and sufficient conditions; rather, they exhibit typicality effects. In this chapter I will suggest that typicality effects, far from being a symptom of some homogeneous underlying cognitive structure, are more plausibly the consequence of some “ecological constraints” acting on the mind. In other words, typicality effects could be the effect of some form of “convergent evolution” between heterogeneous mental structures. This should have important consequences on the role of the notion of “concept” itself: the status of the concept of “concept” in cognitive science should be similar to that of the concept of “fat plant” in botany, which can be of some utility in certain cases, but does not correspond to a genuine botanical kind.

La logica modale è nata per studiare i ragionamenti su ciò che è possibile e ciò che è necessario. Negli ultimi decenni, a partire dal lavoro di logici e filosofi quali Rudolf Carnap, Saul Kripke e David Lewis, la sua applicazione è stata progressivamente estesa ad altri ambiti, quali il ragionamento sul tempo, sulla conoscenza e sui sistemi di norme. Queste ricerche hanno condotto a un complesso e intrigante dialogo con alcune fondamentali branche della filosofia: la metafisica, l’epistemologia, la filosofia del linguaggio. Lo scopo del volume è offrire una panoramica di questo dialogo al contempo accessibile e rigorosa, pensata sia per gli studenti di un corso universitario, sia per il lettore non specialista. Se da un lato tutte le necessarie nozioni tecniche sono rese accessibili ai non addetti ai lavori, dall'altro si restituisce un'immagine fedele delle sfide concettuali che la ricerca in questi settori è oggi chiamata ad affrontare.

In this article we question the utility of the distinction between conceptual and nonconceptual content in cognitive science, and in particular, in the empirical study of visual perception. First, we individuate some difficulties in characterizing the notion of “concept” itself both in the philosophy of mind and cognitive science. Then we stress the heterogeneous nature of the notion of nonconceptual content and outline the complex and ambiguous relations that exist between the conceptual/nonconceptual duality and other pairs of notions, such as top–down/bottom-up and modular/nonmodular. Finally we look in greater detail at the proposal developed by Jacob and Jeannerod (Ways of seeing. The scopes and limits of visual cognition. Oxford, UK: Oxford University Press, 2003 ), who apply the notion of nonconceptual content to empirical research on visual perception. After reconstructing their point of view on concepts, we try to reject their major arguments in support of the conceptual/nonconceptual distinction, i.e. the compositionality of thought and the fineness of grain of percepts.

Pour la plupart des systèmes de représentation de la connaissance orientés concept, l’un des problèmes principaux relève de la commodité technique. A savoir, la représentation de connaissance en termes prototypiques, tout comme la possibilité d’exploiter des formes de raisonnement conceptuel basées sur la typicalité, ne sont pas autorisées. Au contraire, dans les sciences cognitives, il existe des données en faveur de concepts prototypiques, et des formes non-monotoniques de raisonnement conceptuel ont été largement étudiées. Ce fossé cognitif concernant la représentation et le raisonnement constitue un problème pour les systèmes computationnels, puisque l’information prototypique joue un rôle crucial dans plusieurs tâches importantes. Dans la lignée des théories du raisonnement et de la rationalité dites du double processus, nous soutenons que la représentation conceptuelle dans les systèmes computationnels devrait dépendre de deux composantes représentationnelles, chacune spécialisée dans le traitement de différents genres de processus de raisonnement. Dans cet article, nous présentons les avantages computationnels de cette approche en termes de double processus, et les comparons brièvement avec d’autres solutions d’orientation logique, adoptées pour traiter du même problème

The project of neuroaesthetics could be interpreted as an attempt to identify a ?neural essence? of art, i.e., a set of necessary and sufficient conditions formulated in the language of neuroscience, which define the concept art . Some proposals developed within this field can be read in this way. I shall argue that such attempts do not succeed in individuating a neural definition of art. Of course, the fact that the proposals available for defining art in neural terms do not work does not mean that such an enterprise is in principle doomed to failure. However, I maintain that there are good reasons to suspect that in general such a definition cannot be worked out. This does not mean, though, that the study of neural correlates in artwork production and fruition is a senseless project. Neuroaesthetics could succeed in individuating widespread mechanisms common to different forms of art coming from remote cultural contexts, which presumably rely on aspects of our mind and/or brain's functioning that are innate and biologically determined, thus contrasting the idea that artistic phenomena are entirely dependent on cultural factors