Interpretable Policies and the Price of Interpretability in Hypertension Treatment Planning

Problem definition: Effective hypertension management is critical to reducing consequences of atherosclerotic cardiovascular disease, a leading cause of death in the United States. Clinical guidelines for hypertension can be enhanced using decision-analytic approaches, capable of capturing many complexities in treatment planning. However, model-generated recommendations may be uninterpretable/unintuitive, limiting their acceptability in practice. We address this … Read more

Multi-criteria Course Mode Selection and Classroom Assignment Under Sudden Space Scarcity

Problem Definition: While physical (or ‘social’) distancing is an important public health intervention during airborne pandemics, physical distancing dramatically reduces the effective capacity of classrooms. During the COVID-19 pandemic, this presented a unique problem to campus planners who hoped to deliver a meaningful amount of in-person instruction in a way that respected physical distancing. This … Read more

Decomposition Methods for Solving Markov Decision Processes with Multiple Models of the Parameters

We consider the problem of decision-making in Markov decision processes (MDPs) when the reward or transition probability parameters are not known with certainty. We consider an approach in which the decision-maker (DM) considers multiple models of the parameters for an MDP and wishes to find a policy that optimizes an objective function that considers the … Read more

Multi-model Markov Decision Processes

Markov decision processes (MDPs) have found success in many application areas that involve sequential decision making under uncertainty, including the evaluation and design of treatment and screening protocols for medical decision making. However, the usefulness of these models is only as good as the data used to parameterize them, and multiple competing data sources are … Read more

Robust Markov Decision Processes for Medical Treatment Decisions

Medical treatment decisions involve complex tradeoffs between the risks and benefits of various treatment options. The diversity of treatment options that patients can choose over time and uncertainties in future health outcomes, result in a difficult sequential decision making problem. Markov decision processes (MDPs) are commonly used to study medical treatment decisions; however, optimal policies … Read more