Adjusting bias in concept learning

Authors:
Paul E. Utgoff
Affiliations:
Siemens Research and Technology Laboratories, Princeton and Department of Computer Science, Rutgers University, New Brunswick, New Jersey
Venue:
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Year:
1983

Citing 0
Cited 1

Machine lifelong learning: challenges and benefits for artificial general intelligence

AGI'11 Proceedings of the 4th international conference on Artificial general intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

We approach concept learning as a heuristic search through a space of concepts for a concept that satisfies the learning task at hand The heuristics represent bias that the concept learning program employs when forming an inductive generalization. We present a model of bias adjustment and report our experience with an implementation of the model.