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.

Heterogeneous Proxytypes Extended: Integrating Theory-Like Representations and Mechanisms with Prototypes and Exemplars

Antonio Lieto
2019-01-01

Abstract

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.
2019
9th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2018
Prague
22-24 August 2018
Biologically Inspired Cognitive Architectures 2018. BICA 2018, Advances in Intelligent Systems and Computing
Springer Nature
848
217
227
Human-like Intelligence, Knowledge Representation and Reasoning, Categorization, Knowledge Processing, Heterogeneous Proxytypes, Ontologies, Vector Space Models, Bayesian Networks, Cognitive Architectures.
Antonio Lieto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1689315
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