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Intelligent Guessing
May/June 2006 (vol. 21 no. 3)
pp. 74-75
| ASCII Text | x | ||
| Daniel E. O'Leary, "Intelligent Guessing," IEEE Intelligent Systems, vol. 21, no. 3, pp. 74-75, May/June, 2006. | |||
| BibTex | x | ||
| @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 | x | ||
| 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 - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2006.51
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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