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Algorithmic knowledge profiles for introspective monitoring in artificial cognitive agents

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper describes a new approach for the representation of profiles of cognitive functions. The profiles are used in introspective monitoring to keep updated the meta-level about the most relevant attributes of each cognitive function that is executed in the object-level. The profiles are called algorithmic knowledge profiles. Declarative meta-knowledge, procedural meta-knowledge and strategic meta-knowledge are represented using the algorithmic knowledge profile. The profiles are formally defined and the computational implementation is based on extended tabular trees. The approach is illustrated using an instructional planner agent as an example.

Original languageEnglish
Title of host publicationProceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
EditorsYingxu Wang, Freddie Hamdy, Newton Howard, Lotfi A. Zadeh, Amir Hussain, Bernard Widrow
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages475-481
Number of pages7
ISBN (Electronic)9781538607701
DOIs
StatePublished - 14 Nov 2017
Externally publishedYes
Event16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017 - Oxford, United Kingdom
Duration: 26 Jul 201728 Jul 2017

Publication series

NameProceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017

Conference

Conference16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
Country/TerritoryUnited Kingdom
CityOxford
Period26/07/1728/07/17

Keywords

  • algorithmic knowledge profile
  • cognitive computing
  • extended tabular trees
  • introspective monitoring
  • metacognition in computation

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