The metacognitive loop: An architecture for building robust intelligent systems

H. Haidarian, W. Dinalankara, S. Fults, S. Wilson, Don Perlis, M. Schmill, T. Oates, D. P. Josyula, M. L. Anderson

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

10 Scopus citations

Abstract

What commonsense knowledge do intelligent systems need, in order to recover from failures or deal with unexpected situations? It is impractical to represent predetermined solutions to deal with every unanticipated situation or provide predetermined fixes for all the different ways in which systems may fail. We contend that intelligent systems require only a finite set of anomaly-handling strategies to muddle through anomalous situations. We describe a generalized metacognition module that implements such a set of anomaly-handling strategies and that in principle can be attached to any host system to improve the robustness of that system. Several implemented studies are reported, that support our contention.

Original languageEnglish (US)
Title of host publicationCommonsense Knowledge - Papers from the AAAI Fall Symposium, Technical Report
PublisherAI Access Foundation
Pages33-39
Number of pages7
ISBN (Print)9781577354840
StatePublished - 2010
Event2010 AAAI Fall Symposium - Arlington, VA, United States
Duration: Nov 11 2010Nov 13 2010

Publication series

NameAAAI Fall Symposium - Technical Report
VolumeFS-10-02

Other

Other2010 AAAI Fall Symposium
Country/TerritoryUnited States
CityArlington, VA
Period11/11/1011/13/10

All Science Journal Classification (ASJC) codes

  • General Engineering

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