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Anchoring Knowledge in Interaction: Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognition
Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany.
Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany.
City University London, London, UK.
Örebro University, School of Science and Technology.ORCID iD: 0000-0001-8229-1363
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2015 (English)In: Artificial General Intelligence (AGI 2015), Springer, 2015, 35-45 p.Conference paper, Published paper (Refereed)
Abstract [en]

We outline a proposal for a research program leading to a new paradigm, architectural framework, and prototypical implementation, for the cognitively inspired anchoring of an agent's learning, knowledge formation, and higher reasoning abilities in real-world interactions: Learning through interaction in real-time in a real environment triggers the incremental accumulation and repair of knowledge that leads to the formation of theories at a higher level of abstraction. The transformations at this higher level filter down and inform the learning process as part of a permanent cycle of learning through experience, higher-order deliberation, theory formation and revision.

The envisioned framework will provide a precise computational theory, algorithmic descriptions, and an implementation in cyber-physical systems, addressing the lifting of action patterns from the subsymbolic to the symbolic knowledge level, effective methods for theory formation, adaptation, and evolution, the anchoring of knowledge-level objects, realworld interactions and manipulations, and the realization and evaluation of such a system in different scenarios. The expected results can provide new foundations for future agent architectures, multi-agent systems, robotics, and cognitive systems, and can facilitate a deeper understanding of the development and interaction in human-technological settings.

Place, publisher, year, edition, pages
Springer, 2015. 35-45 p.
Series
Lecture Notes in Artificial Intelligence, ISSN 0302-9743 ; 9205
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-46700DOI: 10.1007/978-3-319-21365-1_4ISI: 000363479400004ISBN: 978-3-319-21365-1 (print)ISBN: 978-3-319-21364-4 (print)OAI: oai:DiVA.org:oru-46700DiVA: diva2:873075
Conference
8th International Conference on Artificial General Intelligence (AGI), Berlin, Germany, July 22-25, 2015
Available from: 2015-11-23 Created: 2015-11-23 Last updated: 2017-10-17Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
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