This single day workshop is an excellent forum for presenting and hearing about real-world applications of Bayesian networks. It follows the 28th Int. Conference on Uncertainty in AI, the premier conference for presentation of research on Bayesian technology (Aug 15-17th). The call for papers is now out, with submission deadline May 5th (with a week’s extension very likely!).

The aim of the workshop is to foster discussion and interchange about novel contributions that can speak to both the academic and the larger research community. Accordingly, we seek submissions also from practitioners and tool developers as well as researchers. We welcome submissions describing real world applications, whether as stand-alone BNs or where the BNs are embedded in a larger software system. We encourage authors to address the practical issues involved in developing real-world applications, such as knowledge engineering methodologies, elicitation techniques, defining and meeting client needs, validation processes and integration methods, as well as software tools, including visualization and user interaction techniques to support these activities.

We particularly encourage the submission of papers that address the workshop theme of temporal modeling. Recently communities building dynamic Bayes networks (DBNs) and partially observable MDPs (POMDPs) are coming to realize that they are applying their methods to identical applications. Similarly POMDPs and other probabilistic methods are now established in the field of Automated Planning. Stochastic process models such as continuous time Bayes networks (CTBNs) should also be considered as part of this trend. Adaptive and on-line learning models also fit into this focus.