KASER: A qualitatively fuzzy object-oriented inference engine

S. H. Rubin, R. J. Rush, J. Murthy, M. H. Smith, L. Trajković

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

9 Scopus citations

Abstract

This paper describes a shell that has been developed for the purpose of fuzzy qualitative reasoning. The relation among object predicates is defined by object trees that are fully capable of dynamic growth and maintenance. The qualitatively fuzzy inference engine and the developed expert system can then acquire a virtual-rule space that is exponentially (subject to machine implementation constants) larger than the actual, declared-rule space and with a decreasing non-zero likelihood of error. This capability is called knowledge amplification, and the methodology is named KASER. KASER is an acronym for Knowledge Amplification by Structured Expert Randomization. It can handle the knowledge-acquisition bottleneck in expert systems. KASER represents an intelligent, creative system that fails softly, learns over a network, and has enormous potential for automated decision making. KASERs compute with words and phrases and possess capabilities for metaphorical explanations.

Original languageEnglish
Title of host publication2002 Annual Meeting of the North American Fuzzy Information Processing Society, Proceedings - NAFIPS-FLINT 2002
EditorsOlfa Nasraoui, Jim Keller
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages354-359
Number of pages6
ISBN (Electronic)0780374614
DOIs
StatePublished - 2002
EventAnnual Meeting of the North American Fuzzy Information Processing Society, NAFIPS-FLINT 2002 - New Orleans, United States
Duration: Jun 27 2002Jun 29 2002

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
Volume2002-January

Conference

ConferenceAnnual Meeting of the North American Fuzzy Information Processing Society, NAFIPS-FLINT 2002
Country/TerritoryUnited States
CityNew Orleans
Period06/27/0206/29/02

Keywords

  • Computer architecture
  • Costs
  • Decision making
  • Engines
  • Error correction
  • Expert systems
  • Intelligent networks
  • Intelligent systems
  • Production systems
  • User interfaces

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