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, methodological and technical issues in the field of Cognitively-Inspired Artificial Intelligence, (...) Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realise biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biologically and cognitive accuracy of artificial systems in order project and predict their explanatory power with respect to the natural systems taken as source of inspiration. -/- Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science. (shrink)

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) v 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. (shrink)

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 but, on the other hand, require a mechanism for the (...) automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures. (shrink)

In this paper we identify and characterize an analysis of two problematic aspects affecting the representational level of cognitive architectures (CAs), namely: the limited size and the homogeneous typology of the encoded and processed knowledge. We argue that such aspects may constitute not only a technological problem that, in our opinion, should be addressed in order to build arti cial agents able to exhibit intelligent behaviours in general scenarios, but also an epistemological one, since they limit the plausibility of the (...) comparison of the CAs' knowledge representation and processing mechanisms with those executed by humans in their everyday activities. In the fi nal part of the paper further directions of research will be explored, trying to address current limitations and future challenges. (shrink)

We intoduce a novel extension of Description Logics (DLs) of typicality by means of probabilities able to represent and reason about typical properties and defeasible inheritance in DLs.

In actuarial parlance, the price of an insurance policy is considered fair if customers bearing the same risk are charged the same price. The estimate of this fair amount hinges on the expected value obtained by weighting the different claims by their probability. We argue that, historically, this concept of actuarial fairness originates in an Aristotelian principle of justice in exchange (equality in risk). We will examine how this principle was formalized in the 16th century and shaped in life insurance (...) during the following two hundred years, in two different interpretations. The Domatian account of actuarial fairness relied on subjective uncertainty: An agreement on risk was fair if both parties were equally ignorant about the chances of an uncertain event. The objectivist version grounded any agreement on an objective risk estimate drawn from a mortality table. We will show how the objectivist approach collapsed in the market for life annuities during the 18th century, leaving open the question of why we still speak of actuarial fairness as if it were an objective expected value. (shrink)

The proposal of moral enhancement as a valuable means to face the environmental, technological and social challenges that threaten the future of humanity has been criticized by a number of authors. One of the main criticisms has been that moral enhancement would diminish our freedom. It has been said that moral enhancement would lead enhanced people to lose their ‘freedom to fall’, that is, it would prevent them from being able to decide to carry out some morally bad actions, and (...) the possibility to desire and carry out these bad actions is an essential ingredient of free will, which would thus be limited or destroyed—or so the argument goes. In this paper we offer an answer to this criticism. We contend that a morally enhanced agent could lose the ‘freedom to fall’ without losing her freedom for two reasons. First, because we do not consider that a morally well-educated person, for whom the ‘freedom to fall’ is a remote option, is less free than an evildoer, and there is no reason to suppose that bioenhancement introduces a significant difference here. Second, because richness in the amount of alternative possibilities of action may be restored if the stated loss is compensated with an improvement in sensitivity and lucidity that can lead to seeing new options and nuances in the remaining possible actions. (shrink)

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 concept (...) combination. We show that the complexity of reasoning in our logic is EXPTIME-complete as in ALC. (shrink)

We defend, from a contractarian perspective, that the fair price of an insurance policy is the amount that the contracting parties agree when they are both equally uncertain about the insured event. Drawing on the approach developed by R. Sugden in _The Community of Advantage_, we answer two standard objections raised against contractarianism in the actuarial sciences: (1) people are not wise enough to assess their actuarial risks; (2) they are not rational enough to decide which insurance policy suits them (...) better. We show under which circumstances people can make fair actuarial agreements, without presupposing any objective risk or rationality benchmarks. (shrink)

The goal of this essay is twofold. First, it provides a quick look at the foundations of modern relational mechanics by tracing its development from Julian Barbour and Bruno Bertotti's original ideas until present-day's pure shape dynamics. Secondly, it discusses the most appropriate metaphysics for pure shape dynamics, showing that relationalism is more of a nuanced thesis rather than an elusive one. The chapter ends with a brief assessment of the prospects of pure shape dynamics in light of quantum physics.

The paper discusses from a metaphysical standpoint the nature of the dependence relation underpinning the talk of mutual action between material and spatiotemporal structures in general relativity. It is shown that the standard analyses of dependence in terms of causation or grounding are ill-suited for the general relativistic context. Instead, a non-standard analytical framework in terms of structural equation modeling is exploited, which leads to the conclusion that the kind of dependence encoded in the Einstein field equations is a novel (...) one. (shrink)

Is attention both necessary and sufficient for consciousness? Call this central question of this treatise, “Q.” We commonly have the experience of consciously paying attention to something, but is it possible to be conscious of something you are not attending to, or to attend to something of which you are not conscious? Where might we find examples of these? This treatise is a quest to find an answer to Q in two parts. Part I reviews the foundations upon which the (...) discourse on Q is built. Different inputs to Q produce different answers. After consideration of the many ways “attention” and “consciousness” have been defined, I settle upon phenomenal consciousness and Executive Attention (defined as a suite of strategies for structuring cognition for further processing implemented by the executive of working memory) as the most interesting inputs to Q, and the ones on which Part II focuses. Attention without consciousness seems relatively easy to establish empirically, but consciousness without attention is much harder. The putative candidates all seem to have major problems, but I build a strong abductive case for the hitherto ignored case of foveal phenomenal overflow. We consciously see far more detail in our foveal fields than we can Executively Attend, although there is a serious obstacle to our ever confirming that empirically—identifying conscious content relies on Executive Attentional report. Triangulating the capacity limitations of attention, consciousness, and working memory strengthens this case for consciousness without attention, and suggests that cognition must work something like my “Witches’ Hat Model,” on which content can become conscious outside of Executive Attention or working memory. I conclude with some reflections on the implications of my arguments for the discourse on Q, and for other discourses such as the ontologies of attention and consciousness, theories of consciousness, some other cognitive concepts, and ethical considerations in humans, animals, and machines. A conclusive answer to Q continues to elude us. It may perhaps be an ultimately insoluble conundrum. But it is the very essence of humanity to seek an answer, and in so doing, to improve our understanding of our own nature: “The proper study of mankind is man.”1. (shrink)

The paper introduces an extension of the proposal according to which conceptual representations in cognitive agents should be intended as heterogeneous proxytypes. The main contribution of this paper is in that it details how to reconcile, under a heterogeneous representational perspective, different theories of typicality about conceptual representation and reasoning. In particular, it provides a novel theoretical hypothesis - as well as a novel categorization algorithm called DELTA - showing how to integrate the representational and reasoning assumptions of the theory-theory (...) of concepts with the those ascribed to the prototype and exemplars-based theories. (shrink)

The term attention has been used to mean so many different things that some have despaired of it being useful at all. This paper is devoted to bringing a modicum of order to the chaos through the time-honored device of categorization. The chief purpose of this paper is to introduce a comprehensive descriptive taxonomy of the nuanced ways the term attention may be employed. It is presented in table form, followed by elucidations and illustrations of each of its items. But (...) first, I offer reasons why a taxonomy of attention is needed and explore some of its possible benefits. After presenting the taxonomy, I sketch by way of example how it might be applied to two interesting questions: is the umbrella term attention still useful?; and, what is it that ties the subdefinitions of attention together yet distinguishes them from other kinds of cognition? (shrink)

Persuasive technologies can adopt several strategies to change the attitudes and behaviors of their users. In this work I synthesize the lessons learned from three empirical case studies on automated persuasion that have been carried out in the last decade in the contexts of: persuasive news recommendations, social robotics, and e-commerce, respectively. In particular, such studies have assessed, in the technological domain, the effects of nudging techniques relying on well known persuasive argumentation schemas and on framing strategies. In discussing the (...) main findings, I will argue that the obtained persuasive effects are due to the fact that such techniques leverage on cognitive mechanisms that refer to the “system 1” types of automatic processes hypothesized in the context of the dual process theory of reasoning. As a consequence of this state of affairs, any automated persuasive systems (used for ethical purposes: e.g. suggesting good health habits) should be able to re-use these types of system 1 strategies in order to gradually take the users in an argumentation territory where system 2 processes can take place. -/- . (shrink)

I will present the rationale followed for the conceptualization and the following development the Dual PECCS system that relies on the cognitively grounded heterogeneous proxytypes representational hypothesis [Lieto 2014]. Such hypothesis allows integrating exemplars and prototype theories of categorization as well as theory-theory [Lieto 2019] and has provided useful insights in the context of cognitive modelling for what concerns the typicality effects in categorization [Lieto, 2021]. As argued in [Lieto et al., 2018b] a pivotal role in this respect is played (...) by the use of the conceptual spaces framework and by its integration with a symbolic knowledge representation layer. (shrink)

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 arti cial 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 using the Newell's own words: "To treat a system at the knowledge level is to treat it as having some knowledge, some goals, and believing it will do whatever is within its power to attain its goals, in so far as its knowledge indicates" [22, p. 13]. In the last decades, the importance of the knowledge level has been historically and system- atically downsized by the research area in cognitive architectures (CAs), whose interests have been mainly focused on the analysis and the development of mechanisms and the processes governing human and (arti cial) cognition. The knowledge level in CAs, however, represents a crucial level of analysis for the development of such arti cial general systems and therefore deserves greater research attention [17]. In the following, we will discuss areas of broad agree- ment and outline the main problematic aspects that should be faced within a Common Model of Cognition [12]. Such aspects, departing from an analysis at the knowledge level, also clearly impact both lower (e.g. representational) and higher (e.g. social) levels. (shrink)

The paper shows how the Bohmian approach to quantum physics can be applied to develop a clear and coherent ontology of non-perturbative quantum gravity. We suggest retaining discrete objects as the primitive ontology also when it comes to a quantum theory of space-time and therefore focus on loop quantum gravity. We conceive atoms of space, represented in terms of nodes linked by edges in a graph, as the primitive ontology of the theory and show how a non-local law in which (...) a universal and stationary wave-function figures can provide an order of configurations of such atoms of space such that the classical space-time of general relativity is approximated. Although there is as yet no fully worked out physical theory of quantum gravity, we regard the Bohmian approach as setting up a standard that proposals for a serious ontology in this field should meet and as opening up a route for fruitful physical and mathematical investigations. (shrink)

Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this paper, we present TCL (typicality-based compositional logic): a probabilistic, non monotonic extension of standard Description Logics of typicality, and will show how this framework is able to endow artificial systems of a human-like, commonsense based, concept composition procedure that allows its employment in a number of applications (ranging from computational creativity to goal-based reasoning to recommender systems and affective (...) computing). -/- The framework relies on 3 main ingredients: a non monotonic extension of standard Description Logics (allowing to reason on exceptions to inheritance in standard knowledge bases) a probabilistic extension coming from the field of logic programming (the DISPONTE semantics) a cognitive heuristics known ad HEAD-Modifier determining preference rules for the inheritance mechanisms of the novel concepts to be generated via commonsense rules. -/- We report the obtained results and the lessons learned of this research path in the context of model-based AI applications. -/- . (shrink)

In the last decade Human-Computer Interaction (HCI) has started to focus attention on forms of persuasive interaction where computer technologies have the goal of changing users behavior and attitudes according to a predefined direction. In this work, we hypothesize a strong connection between logical fallacies (forms of reasoning which are logically invalid but cognitively effective) and some common persuasion strategies adopted within web technologies. With the aim of empirically evaluating our hypothesis, we carried out a pilot study on a sample (...) of 150 e-commerce websites. (shrink)

We present a new metaphysical framework for physics that is conceptually clear, ontologically parsimonious, and empirically adequate. This framework relies on the notion of self-subsisting structure, that is, a set of fundamental physical elements whose individuation and behavior are described in purely relational terms, without any need for a background spacetime. Although the specification of the fundamental elements of the ontology depends on the particular physical domain considered---and is thus susceptible to scientific progress---, the empirically successful structural features of the (...) framework are preserved through theory change. The kinematics and dynamics of these self-subsisting structures are technically implemented using the theoretical framework of Pure Shape Dynamics, which provides a completely relational physical description of a system in terms of the intrinsic geometry of a suitably defined space called shape space. (shrink)

The paper discusses the possible implications of the relational framework of Pure Shape Dynamics for the metaphysics of time. The starting point of the analysis is an interpretation of shapes in ontic structural realist terms, which gives rise to the notion of self-subsisting structure. The relational version of a Newtonian-particle toy model is introduced and discussed as a concrete example.

The paper presents an extension of the metaphysics of self-subsisting structures set out in a companion paper to the realm of non-relativistic quantum physics. The discussion is centered around a Pure Shape Dynamics model representing a relational implementation of a de Broglie-Bohm N-body system. An interpretation of this model in terms of self-subsisting structures is proposed and assessed against the background of the debate on the metaphysics of quantum physics, with a particular emphasis on the nature of the wave function. (...) The analysis shows that elaborating an appropriate Leibnizian/Machian metaphysics of the quantum world requires a substantial revision of the notion of world-building relation. (shrink)

Exploramos aquí la conexión entre los conceptos de riesgo e igualdad en el argumento del observador imparcial. La concepción de la justicia que elegiría un observador imparcial se justifica por la pureza del procedimiento de elección. Sin embargo, si modelizamos esta decisión utilizando medidas del riesgo habituales en matemática financiera, veremos cómo el criterio de elección del observador bajo el velo de la ignorancia contiene una preferencia implícita por el grado de desigualdad resultante. Esto nos obliga a reconsiderar la pureza (...) procedimental de la elección. (shrink)

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual (...) structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and –in addition– that it may be plausibly applied to different general computational models of cognition. The current version of the system, in fact, extends our previous work, in that Dual-PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation. (shrink)

In this article, I argue that the artificial components of hybrid bionic systems do not play a direct explanatory role, i.e., in simulative terms, in the overall context of the systems in which they are embedded in. More precisely, I claim that the internal procedures determining the output of such artificial devices, replacing biological tissues and connected to other biological tissues, cannot be used to directly explain the corresponding mechanisms of the biological component(s) they substitute (and therefore cannot be used (...) to explain the local mechanisms determining an overall biological or cognitive function replicated by such bionic models). I ground this analysis on the use of the Minimal Cognitive Grid (MCG), a novel framework proposed in Lieto (Cognitive design for artificial minds, 2021) to rank the epistemological and explanatory status of biologically and cognitively inspired artificial systems. Despite the lack of such a direct mechanistic explanation from the artificial component, however, I also argue that the hybrid bionic systems can have an indirect explanatory role similar to the one played by some AI systems built by using an overall structural design approach (but including the partial adoption of functional components). In particular, the artificial replacement of part(s) of a biological system can provide i) a local functional account of that part(s) in the context of the overall functioning of the hybrid biological–artificial system and ii) global insights about the structural mechanisms of the biological elements connected to such artificial devices. (shrink)

In the last decades Human-Computer Interaction (HCI) has started to focus attention on “persuasive technologies” having the goal of changing users’ behavior and attitudes according to a predefined direction. In this talk we show how some of the techniques employed in such technologies trigger some well known cognitive biases by adopting a strategy relying on logical fallacies (i.e. forms of reasoning which are logically invalid but psychologically persuasive). In particular, we will show how the mechanisms reducible to logical fallacies are (...) used to design web and mobile interfaces in domains ranging from the e-commerce to the jihadist propaganda. The final part of the talk will be devoted to point out the potential ethical dangers related to the misuse of these techniques in the design of persuasive technologies. (shrink)

In this work we present NERVOUS, an intelligent recommender system exploiting a probabilistic extension of a Description Logic of typicality to dynamically generate novel contents in AllMusic, a comprehensive and in-depth resource about music, providing data about albums, bands, musicians and songs. The tool can be used for both the generation of novel music genres and styles, described by a set of typical properties characterizing them, and the reclassification of the available songs within such new genres.

In this work we present an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework (i.e. the TCL logic, see Lieto & Pozzato 2020) which is based on a human-like procedure for the automatic generation of novel concepts in a Description Logics knowledge base (see also Lieto et al. 2019, Chiodino et al. 2020 for other applications). In particular, in order to model human-like forms of concept (...) combinations, the TCL logic combines a probabilistic description logics of typicality with the HEAD-MODIFIER heuristics coming from cognitive semantics. In the context of our application of such framework, our system exploits the logic TCL to automatically generate novel commonsense semantic representations of compound emotions (e.g. Love as derived from the combination of Joy and Trust according to Plutchik’s theory of emotions, see Plutchik 2001). The generated emotions corresponds to prototypes, i.e. commonsense representations of given concepts, and have been used to reclassify emotion-related contents in a variety of artistic domains. We have tested our system in the context of the H2020 EU project SPICE for providing artistic recommendations of museum items in the Galleria di Arte Moderna (GAM) of Turin. The obtained results (reported in Lieto et al, 2021 and Lieto at al., to appear) show promising results for what concerns both the acceptance of the provided affective recommendation and the explainability associated to each suggestion made by the users. Here we discuss, the open problems and the lessons learned. -/- . (shrink)

The mental rotation ability is an essential spatial reasoning skill in human cognition and has proven to be an essential predictor of mathematical and STEM skills, critical and computational thinking. Despite its importance, little is known about when and how mental rotation processes are activated in games explicitly targeting spatial reasoning tasks. In particular, the relationship between spatial abilities and TetrisTM has been analysed several times in the literature. However, these analyses have shown contrasting results between the effectiveness of Tetris-based (...) training activities to improve mental rotation skills. In this work, we studied whether, and under what conditions, such ability is used in the TetrisTM game by explicitly modelling mental rotation via an ACT-R based cognitive model controlling a virtual agent. The obtained results show meaningful insights into the activation of mental rotation during game dynamics. The study suggests the necessity to adapt game dynamics in order to force the activation of this process and, therefore, can be of inspiration to design learning activities based on TetrisTM or re-design the game itself to improve its educational effectiveness. (shrink)

The 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 (thus extending its categorization capabilities) and, in addition, can provide useful insights in the context of (...) a computationally grounded science of the mind. (shrink)

Las personas somos absolutamente diferentes de las cosas, no cabe ninguna duda al respecto. No obstante, sí debemos diferenciar nítidamente entre los individuos y el concepto de “persona”. Así pues, la persona posee un “horizonte interior”, absolutamente novedoso y que le caracteriza como ser en aproximación a la Verdad y a la Libertad, las cuales no sólo son específicas del propio humano, sino que le son necesarias en cuanto remedios contra la desolación y la tiranía. Asimismo, una sociedad puede ser (...) tiránica en varios sentidos, pero Manuel Mindán sostiene que, para que no lo sea, el individuo entendido como “persona” debe primar siempre sobre el grupo gregario y cerrado. (shrink)

Endowing 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 output). This is due to the fact that the classical problem (...) of opacity in artificial neural networks (ANNs) explodes with the adoption of current Deep Learning techniques [LeCun, Bengio, Hinton, 2015]. In this paper we argue that the explanatory deficit of such techniques represents an important problem, that limits their adoption in the cognitive modelling and computational cognitive science arena. In particular we will show how the current attempts of providing explanations of the deep nets behaviour (see e.g. [Ritter et al. 2017] are not satisfactory. As a possibile way out to this problem, we present two different research strategies. The first strategy aims at dealing with the opacity problem by providing a more abstract interpretation of neural mechanisms and representations. This approach is adopted, for example, by the biologically inspired SPAUN architecture [Eliasmith et al., 2012] and by other proposals suggesting, for example, the interpretation of neural networks in terms of the Conceptual Spaces framework [Gärdenfors 2000, Lieto, Chella and Frixione, 2017]. All such proposals presuppose that the neural level of representation can be considered somehow irrelevant for attacking the problem of explanation [Lieto, Lebiere and Oltramari, 2017]. In our opinion, pursuing this research direction can still preserve the use of deep learning techniques in artificial cognitive models provided that novel and additional results in terms of “transparency” are obtained. The second strategy is somehow at odds with respect to the previous one and tries to address the explanatory issue by avoiding to directly solve the “opacity” problem. In this case, the idea is that one of resorting to pre-compiled plausible explanatory models of the word used in combination with deep-nets (see e.g. [Augello et al. 2017]). We argue that this research agenda, even if does not directly fits the explanatory needs of Computational Cognitive Science, can still be useful to provide results in the area of applied AI aiming at shedding light on the models of interaction between low level and high level tasks (e.g. between perceptual categorization and explanantion) in artificial systems. (shrink)

In this paper a possible general framework for the representation of concepts in cognitive artificial systems and cognitive architectures is proposed. The framework is inspired by the so called proxytype theory of concepts and combines it with the heterogeneity approach to concept representations, according to which concepts do not constitute a unitary phenomenon. The contribution of the paper is twofold: on one hand, it aims at providing a novel theoretical hypothesis for the debate about concepts in cognitive sciences by providing (...) unexplored connections between different theories; on the other hand it is aimed at sketching a computational characterization of the problem of concept representation in cognitively inspired artificial systems and in cognitive architectures. (shrink)

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 risultato di un un doppio esperimento sul campo condotto presso il Liceo Scientifico “Guido Parodi” (...) di Acqui Terme in cui gruppi di studenti paragonano lo strumento della mappa concettuale e quello dell’ontologia nella risoluzione di due problemi di “misconcezione” (o errata concettualizzazione): uno indotto attraverso la consegna di appunti e materiali didattici contenenti informazioni volontariamente contraddittorie tra loro (caso che potrebbe corrispondere alla situazione in cui uno studente prende - per qualche motivo - degli appunti in modo scorretto) e l’altro legato ad una complessità concettuale intrinseca all’argomento. (shrink)

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 categorization and knowledge (...) invention tasks - how cognitively inspired heuristics can help (both in terms of efficiency and efficacy) in the realization of intelligent artificial systems able to reason in a human-like fashion, with results comparable to human-level performances. (shrink)

I will present the rationale followed for the conceptualization and the following development the Dual PECCS system that relies on the cognitively grounded heterogeneous proxytypes representational hypothesis. Such hypothesis allows integrating exemplars and prototype theories of categorization and has provided useful insights in the context of cognitive modelling for what concerns the typicality effects in categorization. As argued in [Chella et al., 2017] [Lieto et al., 2018b] [Lieto et al., 2018a] a pivotal role in this respect is played by the (...) use of the conceptual spaces framework and by its integration with a symbolic knowledge representation layer. (shrink)

Invited Lecture at the SRM ACM Student Chapter, India, on Cognitive Heuristics for Commonsense Thinking and Reasoning in the next generation Artificial Intelligence. The lecture proposes a historical and technical overview of strategies for commonsense reasoning in AI.

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 our application of this logic, the (...) overall pipeline of our system works as follows: given a goal expressed as a set of properties, if the knowledge base does not contain a concept able to fulfill all these properties, then our system looks for two concepts to recombine in order to extend the original knowledge based satisfy the goal. (shrink)

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 representation and processing mechanisms are not sufficiently (...) constrained with insights coming from cognitive science (Lieto 2021; Lieto, Lebiere, Oltramari, 2018). As a possible way out to such knowledge processing issues, I present the main assumptions that have led to the development of the Dual PECCS categorization system (Lieto, Radicioni, Rho 2017) and discuss some of the lessons learned and their possible implications in the design of the knowledge modules and knowledge-processing mechanisms of integrated cognitive architectures. (shrink)

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 important topic of investigation in (...) both these areas, a more comprehensive approach coupling them with narratology, digital humanities and literary studies was still lacking. With the aim of covering this empty space, in the last years, a multidisciplinary effort has been made in order to create an international meeting open to computer scientist, psychologists, digital humanists, linguists, narratologists etc.. This event has been named CMN (for Computational Models of Narrative) and was launched in the 2009 by the MIT scholars Mark A. Finlayson and Patrick H. Winston1. (shrink)

Inventing 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 in a human-like fashion. The proposed approach has (...) been tested both in the task of goal-driven concept invention and has additionally applied within the context of serendipity-based recommendation systems. I will present the obtained results, the lessons learned, and the road ahead of this research path. (shrink)

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 inspirazione cognitiva.

Dynamic 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 both in the task of goal-driven concept invention [2,3] (...) and has additionally applied within the context of serendipity-based recommendation systems [4]. I will present the obtained results, the lessons learned, and the road ahead of this research path. -/- . (shrink)

An ontology of Leibnizian relationalism, consisting in distance relations among sparse matter points and their change only, is well recognized as a serious option in the context of classical mechanics. In this paper, we investigate how this ontology fares when it comes to general relativistic physics. Using a Humean strategy, we regard the gravitational field as a means to represent the overall change in the distance relations among point particles in a way that achieves the best combination of being simple (...) and being informative. (shrink)

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 mechanisms are nowadays used to design web and mobile (...) technologies in domains ranging from e-commerce [4] and news recommendations [1] to the jihadist propaganda. We will also show how and to what extent such persuasive strategies have an impact on nudging the choices of the users in digital environments. (shrink)

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 commonsense reasoning system, built (...) by using insights from cognitive semantics. (shrink)

This work describes an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework.