Beth Goldstein

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The work presented here is part of a research project to develop decision-support software for case managers in the Kentucky social welfare system. Welfare case managers help their clients plan participation in activities such as volunteer work, job readiness programs , substance abuse counselling, or study in high school or college, for example. The case(More)
This paper describes a process by which anthropologists, computer scientists, and social welfare case managers collaborated to build a stochastic model of welfare advising in Kentucky. In the process of collaboration, the research team rethought the Bayesian network model of Markov decision processes and designed a new knowledge elicitation format. We(More)
The project described in this paper originated with an observation by the AI group at the University of Kentucky, that, individually , stochastic planning and constraint satisfaction are well-studied topics that resulted in efficient software, but stochastic planning in the presence of constraints on the domains and actions is an open area of investigation.(More)
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(More)
We describe the " Welfare to Work " scenario, and the software we are designing to support case managers' planning for their clients. President Clinton signed the revised welfare legislation, " Personal Responsibility Work Opportunity Reconciliation Act (PRWORA) " in 1996. This legislation stipulates a set of supports and regulations for welfare recipients(More)
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