Planning for success: The social approach to building Bayesian models

We introduce a new variant of Markov decision processes called MDPs with action results, and a variant of dynamic Bayesian networks called bowties, for modeling the effects of stochastic actions. Bowties grew out of our work on decision-support systems for advisors in the US social welfare system. Bowties, and our elicitation process for them, are designed to elicit dynamic Bayesian network fragments from domain experts who think narratively instead of quantitatively. Our elicitation process has worked well with the welfare case managers and other domain experts, in the sense of capturing consistent and validated models.