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Automated planning problems classically involve finding a sequence of actions that transform an initial state to some state satisfying a conjunctive set of goals with no temporal constraints. But in many real-world problems, the best plan may involve satisfying only a subset of goals or missing defined goal deadlines. For

Automated planning problems classically involve finding a sequence of actions that transform an initial state to some state satisfying a conjunctive set of goals with no temporal constraints. But in many real-world problems, the best plan may involve satisfying only a subset of goals or missing defined goal deadlines. For example, this may be required when goals are logically conflicting, or when there are time or cost constraints such that achieving all goals on time may be too expensive. In this case, goals and deadlines must be declared as soft. I call these partial satisfaction planning (PSP) problems. In this work, I focus on particular types of PSP problems, where goals are given a quantitative value based on whether (or when) they are achieved. The objective is to find a plan with the best quality. A first challenge is in finding adequate goal representations that capture common types of goal achievement rewards and costs. One popular representation is to give a single reward on each goal of a planning problem. I further expand on this approach by allowing users to directly introduce utility dependencies, providing for changes of goal achievement reward directly based on the goals a plan achieves. After, I introduce time-dependent goal costs, where a plan incurs penalty if it will achieve a goal past a specified deadline. To solve PSP problems with goal utility dependencies, I look at using state-of-the-art methodologies currently employed for classical planning problems involving heuristic search. In doing so, one faces the challenge of simultaneously determining the best set of goals and plan to achieve them. This is complicated by utility dependencies defined by a user and cost dependencies within the plan. To address this, I introduce a set of heuristics based on combinations using relaxed plans and integer programming formulations. Further, I explore an approach to improve search through learning techniques by using automatically generated state features to find new states from which to search. Finally, the investigation into handling time-dependent goal costs leads us to an improved search technique derived from observations based on solving discretized approximations of cost functions.
ContributorsBenton, J (Author) / Kambhampati, Subbarao (Thesis advisor) / Baral, Chitta (Committee member) / Do, Minh B. (Committee member) / Smith, David E. (Committee member) / Langley, Pat (Committee member) / Arizona State University (Publisher)
Created2012
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Description
As a medical scribe working in an Emergency Department (ED) at Banner Gateway Medical Center (BGMC), the researcher was able to identify how the work flow and satisfaction of those in the ED would decrease when there were no Physician Assistants (PA's) being utilized during specific shifts. As for other

As a medical scribe working in an Emergency Department (ED) at Banner Gateway Medical Center (BGMC), the researcher was able to identify how the work flow and satisfaction of those in the ED would decrease when there were no Physician Assistants (PA's) being utilized during specific shifts. As for other shifts where PA's were on shift and were being utilized, the work flow would drastically increase, more patients would be seen in less time and the satisfaction of the researchers co-workers would increase. This paradigm of how PA's are implemented brought the researcher to understand the overall success of having Physicians Assistants in partnership with Physicians, consulting physicians and management in the ED. The researcher conducted a five-month long analyses of how implementation of Physician Assistants in the ED could effect overall satisfaction. The researcher looked at the satisfaction of the PAs themselves, attending physicians, nurses, nursing assistants, ED manager, ED director, ED co-director and the patients themselves. The researcher collected questionnaires, conducted interviews and retrieved data from Banner Health Services for the year 2014 to compare her data. The researcher conducted the study both at Banner Gateway Medical Center (BGMC) Emergency Department and also at Banner Baywood Medical Center (BBMC) ED. In comparison of the data collected from BGMC ED to BBMC ED resulted in a significant difference in overall satisfaction based on implementation. Although both emergency departments are owned by the same Banner corporation and only a few miles apart in distance, they implement Pas differently. The difference in the implementation did prove to effect the overall satisfaction. BGMC ED employees as well as manager and patients were more satisfied than those of BBMC ED. Some of the noted differences were that BBMC PAs see more patients per hour, they see higher acuity patients, are less compensated, are placed further apart from their attending physicians and other staff in the ED, there is minimal communication, PAs feel there voice is not heard and they feel pushback on feedback with no plan for improvement. BGMC PAs reported overall increase in satisfaction as compared to BBMC because of the increased communication, placement of PAs within the ED is closer to attending physicians and other staff, they see lower acuity patients, are better compensated and monthly meetings on improvements that can be made and the PAs feel their voice is being heard. Productivity scores for BGMC ED PAs were 1.71 patients per hour as compare to BBMC ED which was 1.86 patients per hour. BBMC PA patient satisfaction on average was 60.6 as compared to BGMC where the PA average satisfaction was 67.8.
ContributorsApplegate, Lauren Mckenzie (Author) / Kashiwagi, Dean (Thesis director) / Coursen, Cristi (Committee member) / Kashiwagi, Jacob (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-05