Edinburgh Research Explorer

Anchoring Knowledge in Interaction: Towards a harmonic subsymbolic/symbolic framework and architecture of computational cognition

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Tarek R. Besold
  • Kai-Uwe Kuehnberger
  • Artur D'Avila Garcez
  • Alessandro Saffiotti
  • Martin Fischer
  • Alan Bundy

Related Edinburgh Organisations

Access status

Open

Documents

http://link.springer.com/chapter/10.1007/978-3-319-21365-1_4
Original languageEnglish
Title of host publicationArtificial General Intelligence
Subtitle of host publication8th International Conference, AGI 2015, AGI 2015, Berlin, Germany, July 22-25, 2015, Proceedings
PublisherSpringer International Publishing
Pages35-45
Number of pages11
ISBN (Electronic)978-3-319-21365-1
ISBN (Print)978-3-319-21364-4
DOIs
StatePublished - 2015

Publication series

NameLecture Notes in Computer Science
Volume9205
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Abstract

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, real-world 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, multiagent systems, robotics, and cognitive systems, and can facilitate a deeper understanding of the development and interaction in human-technological settings.

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