On the Thresholds of Knowledge
Proceedings of the Tenth International Joint Conference on Artificial Intelligence. Panels and Invited Talks. Pages 1173-1181.
Abstract
We articulate the three major findings of AI to date: (1) The Knowledge Principle: if a program is to perform a complex task well, it must know a great deal about the world in which it operates. (2) A plausible extension of that principle, called the Breadth Hypothesis: there are two additional abilities necessary for intelligent behavior in unexpected situations: falling back on increasingly general knowledge, and analogizing to specific but far-flung knowledge. (3) AI as Empirical Inquiry: we must test our ideas experimentally, on large problems. Each of these three hypotheses proposes a particular threshold to cross, which leads to a qualitative change in emergent intelligence. Together, they determine a direction for future AI research.
@inproceedings{ijcai1987p240,
title = {On the Thresholds of Knowledge},
author = {Lenat, Douglas B. and Feigenbaum, Edward A.},
booktitle = {Proceedings of the Tenth International Joint Conference on
Artificial Intelligence, {IJCAI-87}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John McDermott},
pages = {1173--1181},
year = {1987},
note = {Panels and Invited Talks},
url = {https://ijcai.org/proceedings/1987/240},
}
TY - CPAPER TI - On the Thresholds of Knowledge AU - Lenat, Douglas B. AU - Feigenbaum, Edward A. T2 - Proceedings of the Tenth International Joint Conference on Artificial Intelligence, IJCAI-87 PB - International Joint Conferences on Artificial Intelligence PY - 1987 SP - 1173 EP - 1181 UR - https://ijcai.org/proceedings/1987/240 ER -Copied
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