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Contribution to Book
Recognition and resolution of 'comprehension uncertainty' in AI
Intelligent Systems
  • Sukanto Bhattacharya, Deakin University
  • Kuldeep Kumar, Bond University
Date of this Version
1-1-2012
Document Type
Book Chapter
Publication Details

Published version

Bhattacharya, S., & Kumar, K. (2012). Recognition and resolution of 'comprehension uncertainty' in AI. In V.M Koleshko(Ed.). Intelligent Systems (pp.245-256). Croatia: InTech

Access the publisher

2012 HERDC submission. FoR codes: 010401; 080102

© Copyright Vladimir Mikhailovich Koleshko, 2012

ISBN
9789535100546
Abstract
Handling uncertainty is an important component of most intelligent behaviour – so uncertainty resolution is a key step in the design of an artificially intelligent decision system (Clark, 1990). Like other aspects of intelligent systems design, the aspect of uncertainty resolution is also typically sought to be handled by emulating natural intelligence (Halpern, 2003; Ball and Christensen, 2009). In this regard, a number of computational uncertainty resolution approaches have been proposed and tested by Artificial Intelligence (AI) researchers over the past several decades since birth of Al as a scientific discipline in early 1950s post- publication of Alan Turing's landmark paper (Turing, 1950).
Citation Information
Sukanto Bhattacharya and Kuldeep Kumar. "Recognition and resolution of 'comprehension uncertainty' in AI" CroatiaIntelligent Systems (2012) p. 245 - 256
Available at: http://works.bepress.com/kuldeep_kumar/41/