Hypergraph Grammars for Knowledge Based Model Construction
Abstract
Graphical belief networks, including Bayes nets and influence diagrams, can be represented with directed hypergraphs. Each directed hyperedge corresponds to a factor of the joint distribution of all variables in the model. A hyperedge replacement grammar is a collection of rules for replacing hyperedges with hypergraphs. A hyperedge replacement grammar for graphical belief networks defines a collection of graphical belief models. Hyperedge replacement grammars have several interesting implications in the construction of graphical models. (1) They provide a way to represent the process of constructing a graphical model. (2) Coupled with an object-oriented variable type system, provide a convenient method for searching through candidate factors to fill a particular slot in the model graph. (3) They provide a method for integrating high-level and detailed views of a graphical model. (4) They provide a mechanism for representing uncertainty about the model structure.
Cite
Text
Almond. "Hypergraph Grammars for Knowledge Based Model Construction." Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, 1995.Markdown
[Almond. "Hypergraph Grammars for Knowledge Based Model Construction." Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, 1995.](https://mlanthology.org/aistats/1995/almond1995aistats-hypergraph/)BibTeX
@inproceedings{almond1995aistats-hypergraph,
title = {{Hypergraph Grammars for Knowledge Based Model Construction}},
author = {Almond, Russell G.},
booktitle = {Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics},
year = {1995},
pages = {15-22},
volume = {R0},
url = {https://mlanthology.org/aistats/1995/almond1995aistats-hypergraph/}
}