BNet.News
In This Issue: July/August 2006 
•   Charles River Analytics Releases BNet.Builder 1.3
•   BNet.EngineKit User Tip: Undo and Redo
•   Upgrading Your Trial Version of BNet.Builder
•   Reminder: Upcoming UAI 2006 Conference
•   BNet.Builder User Tip: Export to .png Image File
•   Publicize Your Belief Network Success Story
Charles River Analytics Releases BNet.Builder 1.3
CAMBRIDGE, MA - Charles River Analytics recently released version 1.3 of their Bayesian belief network modeling tool, BNet.Builder. BNet.Builder is a desktop application for rapidly creating Belief Networks, entering information, and getting results. BNet.Builder allows users to create models quickly and easily.

Zach Cox, software engineer and chief developer of BNet.Builder notes, “There are a number of useful new features with BNet.Builder 1.3, including support for disconnected Bayesian networks, a faster inference engine (based on source code generation), and the ability to switch between the available inference engines. Also, you can expand/collapse beliefs or evidence on all selected nodes; zoom in/out on monitor nodes; export network, CPT, Belief & Evidence Summary, or Mutual Information to a .png file; and randomize all CPTs.”

BNet.Builder is part of Charles River Analytics' family of Bayesian Network products, including BNet.EngineKit.

BNet.Builder is available directly from Charles River Analytics. For additional information or a free trial version:

* Contact Zach Cox at (617) 491-3474 x523 or e-mail bnet-sales@cra.com

* Or visit: http://www.cra.com/bnet.builder

BNet.Builder
Upgrading Your Trial Version of BNet.Builder
If you've downloaded an earlier trial version of BNet.Builder and want to upgrade to the trial version of BNet.Builder 1.3, follow these steps:

* Uninstall the old version (run the uninstaller from the Start Menu/BNet.Builder/Uninstall BNet.Builder).
* Install the new version (available at http://www.cra.com/bnet.builder).

For the full commercial version of BNet.Builder, visit http://www.cra.com/bnet.builder

BNet.Builder
BNet.Builder User Tip: Export to .png Image File
In the new BNet.Builder 1.3 release you can save your Bayesian network to an image file, which can then be used in publications, documents, and web pages.

To save your Bayesian network to an image file:
* From the Tools menu, select "Export to PNG..."
* Select the option to save as a .png file.

Not only can you export the Bayesian network to a .png file, you can also export the Conditional Probability Table, Belief and Evidence Summary, and Mutual Information views to a .png file as well.

To export the Conditional Probability Table, Belief and Evidence Summary, or Mutual Information views:
* Open the view.
* Click on the title bar to select it
* From the Tools menu, select "Export to PNG..."

To learn more about BNet.Builder 1.3, click here.

BNet.EngineKit User Tip: Undo and Redo
The BayesianNetwork class was designed to be used in an interactive editor (like BNet.Builder) and therefore it provides support for undo and redo operations. The BayesianNetwork class provides an addUndoableEditListener method, which you can use to register an UndoableEditListener (possibly an UndoManager) that will receive notifications when undoable edits occur.

The BayesianNetwork class also provides a number of public inner classes that implement UndoableEdit, like BayesianNetwork.AddNodeEdit. Instances of these classes are passed to the UndoableEditListener and you can then use these public inner classes to undo and redo various changes to the BayesianNetwork object.

To learn more about Engine.Kit, click here.

Bnet.EngineKit
Reminder: Upcoming UAI 2006 Conference
The 22nd Conference on Uncertainty in Artificial Intelligence (UAI 2006) will take place from July 13th - July 16th, 2006, at the Massachusetts Institute of Technology in Cambridge, Massachusetts.

Scientists from Charles River Analytics will be presenting papers and will be available to answer questions about BNet.Builder and BNet.EngineKit.

To learn more about the conference, click here.

Publicize Your Belief Network Success Story
Want to show off your applications of belief networks to others using them in their research? Send us your success stories. We would like to include at least one in each edition of BNet.News.

To send us your story, please contact lcordeiro@cra.com or zcox@cra.com.

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