BNet.News January/February 2008

		BNet™.News

In This Issue:

January/February 2008

•	Subrata Das Authors Book on Decision-Making Agents

•	BNet.Builder and BNet.EngineKit User Tips

•	BNet.Builder 2.0 and BNet.EngineKit 2.0 - Beta Testers

•	View Back Issues of BNet.News

•	The Sixth Annual Bayesian Modeling Applications Workshop at UAI-08

•	Publicize Your Belief Network Success Story

Subrata Das Authors Book on Decision-Making Agents

Dr. Subrata Das, Chief Scientist of Government Services at Charles River Analytics, has written, "Foundations of Decision-Making Agents: Logic, Probability and Modality," published by World Scientific/Imperial College Publishing Company in January, 2008. The book includes chapters on Bayesian Belief Networks and Influence Diagrams for Making Decisions.

Synopsis
This self-contained book provides three fundamental and generic approaches (logical, probabilistic, and modal) to representing and reasoning with agent epistemic states, specifically in the context of decision making. Each of these approaches can be applied to the construction of intelligent software agents for making decisions, thereby creating computational foundations for decision-making agents. In addition, the book introduces a formal integration of the three approaches into a single unified approach that combines the advantages of all the approaches. The symbolic argumentation approach to decision making developed in this book, combining logic and probability, offers several advantages over the traditional approach to decision making which is based on simple rule-based expert systems or expected utility theory.

For more information, click here.

BNet.Builder 2.0 and BNet.EngineKit 2.0 - Beta Testers

This spring, we'll release version 2.0 of BNet.Builder and BNet.EngineKit. This release will change the way Bayesian networks are created!

BNet.Builder 2.0 features new tools to specify CPTs using just a few parameters instead of thousands, more realistic modeling using pre-defined node types, and better usability based on human-computer interaction and cognitive engineering research.

BNet.EngineKit 2.0 will also contain many new features, such as an API for access to those CPT-simplifying tools available in BNet.Builder and support for Dynamic Bayesian networks to reason about domains that change over time.

We are looking for Beta testers for both products. If you'd like to be one of the first to try the new BNet products, please contact gcatto@cra.com. Be sure to note which product(s), you'd like to test.

To learn more about our BNet products, click here.

The Sixth Annual Bayesian Modeling Applications Workshop at UAI-08

The Sixth Annual Bayesian Modelling Applications Workshop will take place during the Uncertainty in Artificial Intelligence (UAI 2008) conference on July 9, 2008, in Helsinki, Finland. The workshop is an informal forum for those interested in Bayesian modeling. The theme for this year's workshop is "How biased are our numbers?"

Charles River's Dr. Jonathan Pfautz and Sean Guarino are on the workshop committee.

To learn more about the workshop, click here

BNet.Builder and BNet.EngineKit User Tips


BNet.Builder User Tip: Printing You can print the main Bayesian network view at any time by clicking the Print button on the toolbar or selecting the Print item from the file menu. You can also print the Belief and Evidence Summary by selecting it first (just click anywhere in it) and then printing as described above. BNet.EngineKit User Tip: Belief Update Settings You can programmatically control when BNet.EngineKit performs belief updates. First use the BayesianNetwork.getBeliefUpdater() method to obtain its BeliefUpdater object. Then use the BeliefUpdater.setUpdateOnXxx() methods to control which events cause EngineKit to update beliefs. There are also setUpdateOnEvidence() and setUpdateOnAnything() convenience methods to reduce the number of calls you need to typically make.

View Back Issues of BNet.News

We have back issues of BNet.News posted on our Web site. If you're a new subscriber or are looking for more articles and tips, come visit our Web site.

To visit the BNet.News archive, 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 gcatto@cra.com.

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