TY - JOUR
T1 - Rigor mortis
T2 - A response to Nilsson's "Logic and artificial intelligence"
AU - Birnbaum, Lawrence A
N1 - Funding Information:
This paper is based on a talk given at the MIT Workshop on the Foundations of Artificial Intelligence, Dedham, Massachussetts, in June 1987. For many helpful discussions, and for invaluable comments on an earlier draft, I thank Gregg Collins, Jim Firby, Andrew Gelsey, Kris Hammond, Steve Hanks, Pat Hayes, Eric Jones, Alex Kass, David Kirsh, Paul Kube, Stan Letovsky, Nils Niisson, Jordan Pollack, Chris Riesbeck, and Roger Schank. I owe a special debt to Drew McDermott for his many valiant attempts to set me straight, and for putting up with my attempts to set him straight. This work was supported in part by the Defense Advanced Research Projects Agency, monitored by the Office of Naval Research under contract N00014-85-K-0108 and by the Air Force Office of Scientific Research under contract F49620-88-C-0058. The Institute for the Learning Sciences was established in 1989 with the support of Andersen Consulting, part of The Arthur Andersen Worldwide Organization.
PY - 1991/1
Y1 - 1991/1
N2 - Logicism has contributed greatly to progress in AI by emphasizing the central role of mental content and representational vocabulary in intelligent systems. Unfortunately, the logicists' dream of a completely use-independent characterization of knowledge has drawn their attention away from these fundamental AI problems, leading instead to a concentration on purely formalistic issues in deductive inference and model-theoretic "semantics". In addition, their failure to resist the lure of formalistic modes of expression has unnecessarily curtailed the prospects for intellectual interaction with other AI researchers.
AB - Logicism has contributed greatly to progress in AI by emphasizing the central role of mental content and representational vocabulary in intelligent systems. Unfortunately, the logicists' dream of a completely use-independent characterization of knowledge has drawn their attention away from these fundamental AI problems, leading instead to a concentration on purely formalistic issues in deductive inference and model-theoretic "semantics". In addition, their failure to resist the lure of formalistic modes of expression has unnecessarily curtailed the prospects for intellectual interaction with other AI researchers.
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U2 - 10.1016/0004-3702(91)90050-T
DO - 10.1016/0004-3702(91)90050-T
M3 - Article
AN - SCOPUS:0026001868
VL - 47
SP - 57
EP - 77
JO - Artificial Intelligence
JF - Artificial Intelligence
SN - 0004-3702
IS - 1-3
ER -