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  1. Book: Cognitive Design for Artificial Minds.Antonio Lieto - 2021 - London, UK: Routledge, Taylor & Francis Ltd.
    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, (...)
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  • DELTA: A Unifying Categorization Algorithm Integrating Prototypes, Exemplars and Theory-Theory Representations and Mechanisms.Antonio Lieto - 2018 - In Proceedings of AISC 2018, Extended Abstracts. 27100 Pavia, Province of Pavia, Italy: pp. 5-7.
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  • Categorization in Real-World Tasks.Alisa Vokert, Jona Schroder & Alexandra Kirsh - 2020 - In Proceedings of ACS. New York, NY, USA: pp. 37-54.
    We examine the role of category representations for decision-making in real-life tasks. To this end, we empirically examine how people categorize kitchen objects and make use of categories when storing objects in a kitchen. We then compare two computational models and their ability to represent the participants’ mental models. We discuss the advantages and disadvantages of the models and point the way to further research.
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  • Beyond Subgoaling: A Dynamic Knowledge Generation Framework for Creative Problem Solving in Cognitive Architectures.Antonio Lieto - 2019 - Cognitive Systems Research 58:305-316.
    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 (...)
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  • Heterogeneous Proxytypes as a Unifying Cognitive Framework for Conceptual Representation and Reasoning in Artificial Systems.Antonio Lieto - 2021 - In CARLA @FOIS Proceeding. Amsterdam, Netherlands: IOS Press.
    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 (...)
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  • Bounded Rationality and Heuristics in Humans and in Artificial Cognitive Systems.Antonio Lieto - 2019 - Isonomía. Revista de Teoría y Filosofía Del Derecho 1 (4):1-21.
    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 (...)
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  • Dual PECCS: A Cognitive System for Conceptual Representation and Categorization.Antonio Lieto, Daniele Radicioni & Valentina Rho - 2017 - Journal of Experimental and Theoretical Artificial Intelligence 29 (2):433-452.
    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 (...)
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  • Heterogeneous Proxytypes Extended: Integrating Theory-Like Representations and Mechanisms with Prototypes and Exemplars.Antonio Lieto - 2018 - In Advances in Intelligent Systems and Computing: Proceedings of BICA. Springer.
    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 (...)
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