|
|
| |
Artificial Intelligence Vol. 41, No. 3, 2002
Order No. G321-0146 |
|
Half a century ago, at the dawn of the computer era, predictions were made that by this time we would have thinking machines that would compete in their capabilities with the human mind. Although these goals have not been reached, the field of artificial intelligence has made significant progress, as this issue illustrates. The issue contains 13 papers describing advances in many practical technologies such as data mining, machine learning, and multi-agent systems. In addition, a discussion on machine intelligence and the Turing Test is followed by a road map to future work in artificial intelligence by a group of researchers that includes J. McCarthy, M. Minsky, and A. Sloman. |
 |
| |
|
|
click to enlarge  |
 |
|
|
|
|
|
|
 |
|
|
|
|
|
|
 |
|
HTML |
|
|
|
|
|
|
 |
|
|
Papers may be viewed by clicking on the title of interest |
|
|
|
|
|
|
 |
|
Message from the Vice President, Services and Software, Research Division |
|
Alfred Spector |
|
|
|
|
|
|
|
 |
|
|
|
|
|
|
|
|
Preface |
|
Se June Hong, John J. Ritsko, and Alex Birman |
p. 328 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Architectures for intelligent systems |
|
J. F. Sowa |
p. 331 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
ABLE: A toolkit for building multiagent autonomic systems |
|
J. P. Bigus, D. A. Schlosnagle, J. R. Pilgrim, W. N. Mills III, and Y. Diao |
p. 350 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Intelligent probing: A cost-effective approach to fault diagnosis in computer networks |
|
M. Brodie, I. Rish, and S. Ma |
p. 372 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Using a constraint satisfaction formulation and solution techniques for random test program generation |
|
E. Bin, R. Emek, G. Shurek, and A. Ziv |
p. 386 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Using fuzzy control to maximize profits in service level management |
|
Y. Diao, J. L. Hellerstein, and S. Parekh |
p. 403 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Automated generation of model cases for help-desk applications |
|
S. M. Weiss and C. V. Apte |
p. 421 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
A decision-tree-based symbolic rule induction system for text categorization |
|
D. E. Johnson, F. J. Oles, T. Zhang, and T. Goetz |
p. 428 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
A probabilistic estimation framework for predictive modeling analytics |
|
C. V. Apte, R. Natarajan, E. P. D. Pednault, and F. Tipu |
p. 438 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Cross training and its application to skill mining |
|
D. A. Oblinger, M. Reid, M. Brodie, and R. de Salvo Braz |
p. 449 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Predictive algorithms in the management of computer systems |
|
R. Vilalta, C. V. Apte, J. L. Hellerstein, S. Ma, and S. M. Weiss |
p. 461 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Discovering actionable patterns in event data |
|
J. L. Hellerstein, S. Ma, and C.-S. Perng |
p. 475 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Machine learning in a multimedia document retrieval framework |
|
M. P. Perrone, G. F. Russell, and A. Ziq |
p. 494 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Applying machine learning to automated information graphics generation |
|
M. X. Zhou, S. Ma, and Y. Feng |
p. 504 |
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Technical forum
|
|
|
p. 524 |
|
|
|
|
|
|
|
|
Machine intelligence and the Turing Test |
|
I. Brackenbury and Y. Ravin |
|
|
|
|
|
|
|
|
|
An architecture of diversity for commonsense reasoning |
|
J. McCarthy, M. Minsky, A. Sloman, L. Gong, T. Lau, L. Morgenstern, E. T. Mueller, D. Riecken, M. Singh, and P. Singh |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
 |
|
Books |
|
|
p. 540 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
