— Ann E Nicholson
The proceedings of our recent workshop on applying Bayesian networks to real-world problems will be coming out soon (a preliminary version is available for on-line viewing here). The workshop was co-located with the 28th Conference on Uncertainty in Artificial Intelligence (UAI 2012), on Catalina Island, California on August 18, 2012.
Bayesian networks are by now a well-established technology for reasoning under uncertainty, supported by numerous mature academic and commercial software tools. They are being applied in many domains, for example, environmental and ecological modelling, bioinformatics, medical decision support, many types of engineering, robotics, military, financial and economic modelling, education, forensics, emergency response, and surveillance. This workshop solicited submissions describing real-world applications, whether as stand-alone BNs or BNs embedded in larger software systems. We suggested authors address the practical issues involved in developing the applications, such as knowledge engineering methodologies, elicitation techniques, defining and meeting client needs, validation processes and integration methods, as well as software tools to support these activities.
The resultant workshop included presentations on a good variety of applications, including oil drilling, managing river catchments, analysing HIV mutations, gang violence, and understanding students' reading comprehension. Many of the applications responded to a workshop theme by illustrating models of temporal reasoning, using dynamic Bayesian networks (DBNs), continuous-time Bayesian networks (CTBNs) and partially observable MDPs (POMDPs).
The workshop demonstrated an active and growing community of modellers taking what were until recently research techniques for Bayesian modelling and applying them to solving a diverse range of important problems in the wider community.