Cart (Loading....) | Create Account
Close category search window
 

Justifying multiply sectioned Bayesian networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Xiang, Y. ; Massachusetts Univ., Amherst, MA, USA ; Lesser, V.

We consider multiple agents whose task is to determine the true state of an uncertain domain so they can act properly. If each agent only has partial knowledge about the domain and local observation, how can agents accomplish the task with the least amount of communication? Multiply sectioned Bayesian networks (MSBNs) provide an effective and exact framework for such a task but also impose a set of constraints. The most notable is the hypertree agent organization which prevents an agent from communicating directly with arbitrarily another agent. Are there simpler frameworks with the same performance but with less restrictions? We identify a small set of high level choices which logically imply the key representational choices made in MSBNs. The result addresses concerns regarding the necessity of restrictions of the framework. It facilitates comparison with related frameworks and provides guidance to extension of the framework as to what can or cannot be traded off

Published in:

MultiAgent Systems, 2000. Proceedings. Fourth International Conference on

Date of Conference:

2000

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.