KUKU

KU ScholarWorks

  • myKU
  • Email
  • Enroll & Pay
  • KU Directory
    • Login
    View Item 
    •   KU ScholarWorks
    • Business, School of
    • School of Business Scholarly Works
    • View Item
    •   KU ScholarWorks
    • Business, School of
    • School of Business Scholarly Works
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials

    Thumbnail
    View/Open
    UAI04.pdf (273.0Kb)
    Issue Date
    2004-07
    Author
    Cobb, Barry R.
    Shenoy, Prakash P.
    Publisher
    Association for Uncertainty in Artificial Intelligence
    Format
    279654 bytes
    Type
    Book chapter
    Metadata
    Show full item record
    Abstract
    Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for representing continuous chance variables in influence diagrams. Also, MTE potentials can be used to approximate utility functions. This paper introduces MTE influence diagrams, which can represent decision problems without restrictions on the relationships between continuous and discrete chance variables, without limitations on the distributions of continuous chance variables, and without limitations on the nature of the utility functions. In MTE influence diagrams, all probability distributions and the joint utility function (or its multiplicative factors) are represented by MTE potentials and decision nodes are assumed to have discrete state spaces. MTE influence diagrams are solved by variable elimination using a fusion algorithm.
    Description
    This is a short 9-pp version of a longer un-published working paper titled "Decision Making with Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials," School of Business Working Paper No. 304, May 2004, Lawrence, KS.
    URI
    http://hdl.handle.net/1808/151
    ISBN
    0-9749039-0-6
    Collections
    • Distinguished Professors Scholarly Works [918]
    • School of Business Scholarly Works [213]
    Citation
    M. Chickering and J. Halpern (eds.), Uncertainty in Artificial Intelligence (UAI-04), 2004, pp. 85--93, AUAI Press, Arlington, VA

    Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.


    We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.


    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    Browse

    All of KU ScholarWorksCommunities & CollectionsThis Collection

    My Account

    Login

    Statistics

    View Usage Statistics

    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    The University of Kansas
      Contact KU ScholarWorks
    Lawrence, KS | Maps
     
    • Academics
    • Admission
    • Alumni
    • Athletics
    • Campuses
    • Giving
    • Jobs

    The University of Kansas prohibits discrimination on the basis of race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression and genetic information in the University’s programs and activities. The following person has been designated to handle inquiries regarding the non-discrimination policies: Director of the Office of Institutional Opportunity and Access, IOA@ku.edu, 1246 W. Campus Road, Room 153A, Lawrence, KS, 66045, (785)864-6414, 711 TTY.

     Contact KU
    Lawrence, KS | Maps