Uncertainty in Artificial Intelligence
First Name   Last Name   Password   Forgot Password   Log in!
    Proceedings         Authors   Author's Info   Article details         Search    
Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information
Sampath Srinivas, Stuart Russell, Alice Agogino
Abstract:
An algorithm for automated construction of a sparse Bayesian network given an unstructured probabilistic model and causal domain information from an expert has been developed and implemented. The goal is to obtain a network that explicitly reveals as much information regarding conditional independence as possible. The network is built incrementally adding one node at a time. The expert's information and a greedy heuristic that tries to keep the number of arcs added at each step to a minimum are used to guide the search for the next node to add. The probabilistic model is a predicate that can answer queries about independencies in the domain. In practice the model can be implemented in various ways. For example, the model could be a statistical independence test operating on empirical data or a deductive prover operating on a set of independence statements about the domain.
Keywords: null
Pages: 295-308
PS Link:
PDF Link: /papers/89/p295-srinivas.pdf
BibTex:
@INPROCEEDINGS{Srinivas89,
AUTHOR = "Sampath Srinivas and Stuart Russell and Alice Agogino",
TITLE = "Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information",
BOOKTITLE = "Uncertainty in Artificial Intelligence 5 Annual Conference on Uncertainty in Artificial Intelligence (UAI-89)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1989",
PAGES = "295--308"
}


hosted by DSL   •   site info   •   help