Conceptual Spaces for Cognitive Architectures: A Lingua Franca for Different Levels of Representation

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Authors Antonio Lieto, Antonio Chella, Marcello Frixione arXiv ID 1701.00464 Category cs.AI: Artificial Intelligence Citations 58 Venue Biologically Inspired Cognitive Architectures Last Checked 3 months ago
Abstract
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 [Laird (2012)]) adopt a classical symbolic approach, some (e.g. LEABRA [O'Reilly and Munakata (2000)]) are based on a purely connectionist model, while others (e.g. CLARION [Sun (2006)] 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 [Kurup and Chandrasekaran (2007)]. In this paper we propose a reflection on the role that Conceptual Spaces, a framework developed by Peter GΓ€rdenfors [GΓ€rdenfors (2000)] 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 GΓ€rdenfors [GΓ€rdenfors (1997)] for defending the need of a conceptual, intermediate, representation level between the symbolic and the sub-symbolic one.
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