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Intelligent Guessing
May/June 2006 (vol. 21 no. 3)
pp. 74-75
ASCII Text
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Daniel E. O'Leary, "Intelligent Guessing," IEEE Intelligent Systems, vol. 21, no. 3, pp. 74-75, May/June, 2006.
 
 
BibTex
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@article{ 10.1109/MIS.2006.51,
author = {Daniel E. O'Leary},
title = {Intelligent Guessing},
journal ={IEEE Intelligent Systems},
volume = {21},
number = {3},
issn = {1541-1672},
year = {2006},
pages = {74-75},
doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2006.51},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - MGZN
JO - IEEE Intelligent Systems
TI - Intelligent Guessing
IS - 3
SN - 1541-1672
SP74
EP75
EPD - 74-75
A1 - Daniel E. O'Leary,
PY - 2006
KW - artificial intelligence
KW - research and development
VL - 21
JA - IEEE Intelligent Systems
ER -
 
Daniel E. O'Leary, University of Southern California
Guessing is what we do when logic and information don't provide sufficient insight to answer a question completely. Current theories and research on intelligent guessing?that is, guessing that's tied to a rational process?are limited and disjoint. An integrated theory of intelligent guessing could provide an organizing theme for research currently performed under multiple AI subdisciplines.This article is part of a special issue on the Future of AI.
Index Terms:
artificial intelligence, research and development
Citation:
Daniel E. O'Leary, "Intelligent Guessing," IEEE Intelligent Systems, vol. 21, no. 3, pp. 74-75, May/June 2006, doi:10.1109/MIS.2006.51
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