Learning by discovering conflicts

George V. Lashkia, Laurence Anthony

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

Abstract

The paper describes a novel approach to inductive learning based on a 'conflict estimation based learning' (CEL) algorithm. CEL is a new learning strategy, and unlike conventional methods CEL does not construct explicit abstractions of the target concept Instead, CEL classifies unknown examples by adding them to each class of the training examples and measuring how much noise is generated. The class that results in the least noise, i.e., the class that least conflicts with the given example is chosen as the output. In this paper, we describe the underlying principles behind the CEL algorithm, a methodology for its construction, and then summarize convincing empirical evidence mat suggests that CEL can be a perfect solution in real-world decision making applications.

Original languageEnglish
Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
EditorsY. Xiang, B. Chaib-draa
Pages492-497
Number of pages6
Volume2671
Publication statusPublished - 2003
Externally publishedYes
Event16th Conference of the Canadian Society for Computational Studies of Intelligence - Halifax, Canada
Duration: 2003 Jun 112003 Jun 13

Other

Other16th Conference of the Canadian Society for Computational Studies of Intelligence
CountryCanada
CityHalifax
Period03/6/1103/6/13

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ASJC Scopus subject areas

  • Hardware and Architecture

Cite this

Lashkia, G. V., & Anthony, L. (2003). Learning by discovering conflicts. In Y. Xiang, & B. Chaib-draa (Eds.), Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2671, pp. 492-497)