Work

From influence diagrams to multi-operator cluster DAGs

Year: 2012

Type: preprint

Abstract: There exist several architectures to solve influence diagrams using local computations, such as the Shenoy-Shafer, the HUGIN, or the Lazy Propagation architectures. They all extend usual variable elimination algorithms thanks to the use of so-called 'potentials'. In this paper, we introduce a new architecture, called the Multi-operator Cluster DAG architecture, which can produce decompositions with an improved constrained induced-width, and therefore induce potentially exponential gains. Its principle is to benefit from the composite nature of influence diagrams, instead of using uniform potentials, in order to better analyze the problem structure.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1206.6844

Authors: Pralet, Cedric, Schiex, Thomas, Verfaillie, Gerard

Institutions: Centre National de la Recherche Scientifique, Laboratoire d'Analyse et d'Architecture des Systèmes, Institut National de la Recherche Agronomique, Office National d'Études et de Recherches Aérospatiales

Language: English

Topic: Bayesian Modeling and Causal Inference

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1563528785

Cites: 7

Cited by: 4

Related to: 10