English

A Framework for Control Strategies in Uncertain Inference Networks

Artificial Intelligence 2013-04-15 v1

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

Cite

@article{arxiv.1304.3435,
  title  = {A Framework for Control Strategies in Uncertain Inference Networks},
  author = {Moshe Ben-Bassat and Oded Maler},
  journal= {arXiv preprint arXiv:1304.3435},
  year   = {2013}
}

Comments

Appears in Proceedings of the First Conference on Uncertainty in Artificial Intelligence (UAI1985)

R2 v1 2026-06-21T23:58:17.546Z