Uncertainty in Artificial Intelligence
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A Framework for Control Strategies in Uncertain Inference Networks
Moshe Ben-Bassat, Oded Maler
Abstract:
Control Strategies for hierarchical tree-like probabilistic inference networks are formulated and investigated. Strategies that utilize staged look-ahead and temporary focus on subgoals are formalized and refined using the Depth Vector concept that serves as a tool for defining the 'virtual tree' regarded by the control strategy. The concept is illustrated by four types of control strategies for three-level trees that are characterized according to their Depth Vector, and according to the way they consider intermediate nodes and the role that they let these nodes play. INFERENTI is a computerized inference system written in Prolog, which provides tools for exercising a variety of control strategies. The system also provides tools for simulating test data and for comparing the relative average performance under different strategies.
Keywords:
Pages: 143-151
PS Link:
PDF Link: /papers/85/p143-ben-bassat.pdf
BibTex:
@INPROCEEDINGS{Ben-Bassat85,
AUTHOR = "Moshe Ben-Bassat and Oded Maler",
TITLE = "A Framework for Control Strategies in Uncertain Inference Networks",
BOOKTITLE = "Proceedings of the First Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-85)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "1985",
PAGES = "143--151"
}


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