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Case based reasoning as a model for cognitive artificial intelligence.

Craw, Susan; Aamodt, Agnar

Authors

Agnar Aamodt



Contributors

Michael T. Cox
Editor

Peter Funk
Editor

Shahina Begum
Editor

Abstract

Cognitive Systems understand the world through learning and experience. Case Based Reasoning (CBR) systems naturally capture knowledge as experiences in memory and they are able to learn new experiences to retain in their memory. CBR's retrieve and reuse reasoning is also knowledge-rich because of its nearest neighbour retrieval and analogy-based adaptation of retrieved solutions. CBR is particularly suited to domains where there is no well-defined theory, because they have a memory of experiences of what happened, rather than why/how it happened. CBR's assumption that 'similar problems have similar solutions' enables it to understand the contexts for its experiences and the 'bigger picture' from clusters of cases, but also where its similarity assumption is challenged. Here we explore cognition and meta-cognition for CBR through self-refl ection and introspection of both memory and retrieve and reuse reasoning. Our idea is to embed and exploit cognitive functionality such as insight, intuition and curiosity within CBR to drive robust, and even explainable, intelligence that will achieve problemsolving in challenging, complex, dynamic domains.

Citation

CRAW, S. and AAMODT, A. 2018. Case based reasoning as a model for cognitive artificial intelligence. In Cox, M.T., Funk, P. and Begum, S. (eds.) Case-based reasoning research and development: proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Lecture notes in computer science, 11156. Cham: Springer [online], pages 62-77. Available from: https://doi.org/10.1007/978-3-030-01081-2_5

Conference Name 26th International conference on case-based reasoning (ICCBR 2018)
Conference Location Stockholm, Sweden
Start Date Jul 9, 2018
End Date Jul 12, 2018
Acceptance Date May 21, 2018
Online Publication Date Oct 9, 2018
Publication Date Nov 8, 2018
Deposit Date Jun 19, 2018
Publicly Available Date Oct 9, 2018
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer
Pages 62-77
Series Title Lecture notes in computer science
Series Number 11156
Series ISSN 1611-3349
ISBN 9783030010805
DOI https://doi.org/10.1007/978-3-030-01081-2_5
Keywords Cognitive systems; CBR; Memory; Self-reflection
Public URL http://hdl.handle.net/10059/2955

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