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URN: urn:nbn:de:0030-drops-16069
URL: http://drops.dagstuhl.de/opus/volltexte/2008/1606/

Petrou, Maria

The Tower of Knowledge: a novel architecture for organising knowledge combining logic and probability

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Abstract

It is argued that the ability to generalise is the most important characteristic of learning and that generalisation may be achieved only if pattern recognition systems learn the rules of meta-knowledge rather than the labels of objects. A structure, called "tower of knowledge'', according to which knowledge may be organised, is proposed. A scheme of interpreting scenes using the tower of knowledge and aspects of utility theory is also proposed. Finally, it is argued that globally consistent solutions of labellings are neither possible, nor desirable for an artificial cognitive system.

BibTeX - Entry

@InProceedings{petrou:DSP:2008:1606,
  author =	{Maria Petrou},
  title =	{The Tower of Knowledge: a novel architecture for organising knowledge combining logic and probability},
  booktitle =	{Logic and Probability for Scene Interpretation },
  year =	{2008},
  editor =	{Anthony G. Cohn and David C. Hogg and Ralf M{\"o}ller and Bernd Neumann},
  number =	{08091},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2008/1606},
  annote =	{Keywords: Learning by example, learning rules}
}

Keywords: Learning by example, learning rules
Seminar: 08091 - Logic and Probability for Scene Interpretation
Issue date: 2008
Date of publication: 23.10.2008


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