Beth Goldstein

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The glycine receptor (GlyR) is a ligand-gated ion channel and member of the nicotinic acetylcholine receptor superfamily. Acting as allosteric modulators of receptor function, drugs such as alcohol and volatile anesthetics enhance the function of GlyRs. The actions of these drugs at inhibitory receptors in the brain and spinal cord are thought to produce(More)
Glycine receptor function mediates most inhibitory neurotransmission in the brainstem and spinal cord and is enhanced by alcohols, volatile anesthetics, inhaled drugs of abuse, and endogenous compounds including zinc. Because zinc exists ubiquitously throughout the brain, investigations of its effects on the enhancement of GlyR function by alcohols and(More)
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)
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)
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)
planning. During plan examination, the user may alter pref-We introduce a suite of interlinked software tools for eliciting preferences, doing decision-theoretic planning, and displaying the plans. The software allows a user to walk through possible trajectories, adjust preferences, and compare potential trajecto­ ries. This paper focuses on the elicitation(More)
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