Uncertainty in Artificial Intelligence
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Induction, of and by Probability
Larry Rendell
Abstract:
This paper examines some methods and ideas underlying the author's successful probabilistic learning systems(PLS), which have proven uniquely effective and efficient in generalization learning or induction. While the emerging principles are generally applicable, this paper illustrates them in heuristic search, which demands noise management and incremental learning. In our approach, both task performance and learning are guided by probability. Probabilities are incrementally normalized and revised, and their errors are located and corrected.
Keywords: Probabilistic Learning Systems
Pages: 429-443
PS Link:
PDF Link: /papers/85/p429-rendell.pdf
BibTex:
@INPROCEEDINGS{Rendell85,
AUTHOR = "Larry Rendell ",
TITLE = "Induction, of and by Probability",
BOOKTITLE = "Uncertainty in Artificial Intelligence Annual Conference on Uncertainty in Artificial Intelligence (UAI-85)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1985",
PAGES = "429--443"
}


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