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

Authors: Maria Petrou

Published in: Dagstuhl Seminar Proceedings, Volume 8091, Logic and Probability for Scene Interpretation (2008)


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.

Cite as

Maria Petrou. The Tower of Knowledge: a novel architecture for organising knowledge combining logic and probability. In Logic and Probability for Scene Interpretation. Dagstuhl Seminar Proceedings, Volume 8091, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)


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@InProceedings{petrou:DagSemProc.08091.15,
  author =	{Petrou, Maria},
  title =	{{The Tower of Knowledge: a novel architecture for organising knowledge combining logic and probability}},
  booktitle =	{Logic and Probability for Scene Interpretation},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8091},
  editor =	{Anthony G. Cohn and David C. Hogg and Ralf M\"{o}ller and Bernd Neumann},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.08091.15},
  URN =		{urn:nbn:de:0030-drops-16069},
  doi =		{10.4230/DagSemProc.08091.15},
  annote =	{Keywords: Learning by example, learning rules}
}
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