Skip to main content

Solving Probabilistic Networks

  • Chapter
  • 3182 Accesses

Part of the book series: Information Science and Statistics ((ISS))

We build knowledge bases in order to formulate our knowledge about a certain problem domain in a structured way. The purpose of the knowledge base is to support our reasoning about events and decisions in a domain with inherent uncertainty. The fundamental idea of solving a probabilistic network is to exploit the structure of the knowledge base to reason efficiently about the events and decisions of the domain taking the inherent uncertainty into account.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

(2008). Solving Probabilistic Networks. In: Bayesian Networks and Influence Diagrams. Information Science and Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-74101-7_5

Download citation

Publish with us

Policies and ethics