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When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.08091.15
URN: urn:nbn:de:0030-drops-16069
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1606/
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Petrou, Maria
The Tower of Knowledge: a novel architecture for organising knowledge combining logic and probability
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: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.dagstuhl.de/opus/volltexte/2008/1606},
URN = {urn:nbn:de:0030-drops-16069},
doi = {10.4230/DagSemProc.08091.15},
annote = {Keywords: Learning by example, learning rules}
}
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Keywords: |
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Learning by example, learning rules |
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Collection: |
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08091 - Logic and Probability for Scene Interpretation |
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Issue Date: |
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2008 |
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Date of publication: |
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23.10.2008 |
