Modelling Concept Prototype Competencies using a Developmental Memory Model

Author:

Baxter Paul,de Greeff Joachim,Wood Rachel,Belpaeme Tony

Abstract

AbstractThe use of concepts is fundamental to human-level cognition, but there remain a number of open questions as to the structures supporting this competence. Specifically, it has been shown that humans use concept prototypes, a flexible means of representing concepts such that it can be used both for categorisation and for similarity judgements. In the context of autonomous robotic agents, the processes by which such concept functionality could be acquired would be particularly useful, enabling flexible knowledge representation and application. This paper seeks to explore this issue of autonomous concept acquisition. By applying a set of structural and operational principles, that support a wide range of cognitive competencies, within a developmental framework, the intention is to explicitly embed the development of concepts into a wider framework of cognitive processing. Comparison with a benchmark concept modelling system shows that the proposed approach can account for a number of features, namely concept-based classification, and its extension to prototype-like functionality.

Publisher

Walter de Gruyter GmbH

Subject

Behavioral Neuroscience,Artificial Intelligence,Cognitive Neuroscience,Developmental Neuroscience,Human-Computer Interaction

Reference32 articles.

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3. P. Baxter, J. de Greeff, R. Wood, T. Belpaeme, “And what is a Seasnake?”: Modelling the Acquisition of Concept Prototypes in a Developmental Framework, 2nd joint International Conference on Developmental Learning (ICDL) & Epigenetic Robotics, San Diego, USA, IEEE Press, (2012)

4. P. Baxter and W. Browne, Memory as the substrate of cognition: a developmental cognitive robotics perspective, 10th International Conference on Epigenetic Robotics, pp. 19–26, (2010)

5. P. Baxter, R. Wood, A. Morse, and T. Belpaeme, Memory-Centred Architectures: Perspectives on Human-level Cognitive Competencies, AAAI Fall 2011 Symposium on Cognitive Systems, pp. 26–33, (2011)

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