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Indirect sensing through abstractive learning.

journal contribution
posted on 2023-06-07, 14:15 authored by Chris ThorntonChris Thornton
The paper discusses disparity issues in sensing tasks involving the production of a 'high-level' signal from 'low-level' signal sources. It introduces an abstraction theory which helps to explain the nature of the problem and point the way to a solution. It proposes a solution based on the use of supervised adaptive methods drawn from artificial intelligence. Finally, it describes a set of empirical experiments which were carried out to evaluate the efficacy of the method.

History

Publication status

  • Published

Journal

Intelligent Data Analysis

ISSN

1088-467X

Issue

3

Volume

7

Page range

255-266

Department affiliated with

  • Informatics Publications

Notes

Originality: this explores the link between ideas about abstraction and ideas about indirect sensing and is also part of my general project to formulate a sensory informatics. Rigour: the paper uses informal reasoning and some informational calculations. Signification: this is interdisciplinary work relating information theory to cognitive science. Outlet: this is a hard-copy journal (or was at the time) whose status I am not quite sure about. Publisher's version available at official url

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2008-02-29

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