Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Hailfinder. Tools for and experiences with Bayesian normative modeling

W Edwards1

  • 1University of California, Los Angeles, USA. wedwards@mizar.usc.edu

The American Psychologist
|May 8, 1998
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A disease-associated gene desert directs macrophage inflammation through ETS2.

Nature·2024
Same author

British Association of Dermatologists guidelines for biologic therapy for psoriasis 2020: a rapid update.

The British journal of dermatology·2020
Same author

Mr. Edwards, on Ulcers.

The Medical and physical journal·2018
Same author

Incomplete offspring sex bias in Australian populations of the butterfly Eurema hecabe.

Heredity·2016
Same author

A 500-kiloton airburst over Chelyabinsk and an enhanced hazard from small impactors.

Nature·2013
Same author

Treatment of paper mill effluent using an anaerobic/aerobic hybrid side-stream membrane bioreactor.

Water science and technology : a journal of the International Association on Water Pollution Research·2012

Bayes Nets (BNs) and Influence Diagrams (IDs) offer powerful graphical tools for representing complex uncertainties and decisions. Their advancements are enhancing AI and decision-making capabilities, heralding a new era in computing.

Area of Science:

  • Artificial Intelligence
  • Computational Statistics

Background:

  • Bayes Nets (BNs) and Influence Diagrams (IDs) are graphical models for representing uncertainty and decision structures.
  • These tools utilize graphic user interfaces to simplify complex inference and decision-making processes.

Discussion:

  • The Hailfinder BN, designed for severe weather prediction, introduced novel methods for spatial representation, day categorization, and probability elicitation.
  • Key challenges in BN design, including system boundaries and pruning, were addressed.
  • The development of reusable BN fragments is a significant advancement in the technology.

Key Insights:

  • BNs separate structural information from parameters, facilitating Bayesian inference.
  • BNs and IDs are crucial for developing advanced computer technologies, potentially making the 21st century the 'Century of Bayes'.

Related Experiment Videos

  • These models enhance the understanding and performance of complex intellectual tasks.

    • Outlook:

    • Continued rapid technological improvement in BNs is expected.
    • The integration of BNs and IDs will likely drive innovation in AI and computational decision-making.
    • Reusability of BN components will accelerate development and application.