Conceptual Spaces for Cognitive Architectures: A Lingua Franca for Different Levels of Representation
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Abstract (arXiv)
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 G"ardenfors [G"ardenfors (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 G"ardenfors [G"ardenfors (1997)] for defending the need of a conceptual, intermediate, representation level between the symbolic and the sub-symbolic one.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jan 2017.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 1; 2025: 0; 2026: 2.
6 papers.
- 2021A Metamodel and Framework for Artificial General Intelligence From Theory to Practicecited by 5
- 2021Towards a Predictive Processing Implementation of the Common Model of Cognitioncited by 2
- 2023Flexible and Inherently Comprehensible Knowledge Representation for Data-Efficient Learning and Trustworthy Human-Machine Teaming in Manufacturing Environmentscited by 1
- 2024Analogical Reasoning Within a Conceptual Hyperspacecited by 0
- 2026Abstract Concept Modelling in Conceptual Spaces: A Study on Chess Strategiescited by 0
- 2026Forgetting Our Way to Shared Meaning: Effects of Forgetting on Conceptual Alignment in a Non-Partnership Coordination Gamecited by 0
- 2026Forgetting Our Way to Shared Meaning: Effects of Forgetting on Conceptual Alignment in a Non-Partnership Coordination Game13 Jul 2026
- 2026Abstract Concept Modelling in Conceptual Spaces: A Study on Chess Strategies29 Jan 2026
- 2024Analogical Reasoning Within a Conceptual Hyperspace13 Nov 2024
- 2023Flexible and Inherently Comprehensible Knowledge Representation for Data-Efficient Learning and Trustworthy Human-Machine Teaming in Manufacturing Environments19 May 2023
- 2021Towards a Predictive Processing Implementation of the Common Model of Cognition15 May 2021
- 2021A Metamodel and Framework for Artificial General Intelligence From Theory to Practice11 Feb 2021