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- All Subjects: Machine Learning
Description
In this project, the use of deep neural networks for the process of selecting actions to execute within an environment to achieve a goal is explored. Scenarios like this are common in crafting based games such as Terraria or Minecraft. Goals in these environments have recursive sub-goal dependencies which form a dependency tree. An agent operating within these environments have access to low amounts of data about the environment before interacting with it, so it is crucial that this agent is able to effectively utilize a tree of dependencies and its environmental surroundings to make judgements about which sub-goals are most efficient to pursue at any point in time. A successful agent aims to minimizes cost when completing a given goal. A deep neural network in combination with Q-learning techniques was employed to act as the agent in this environment. This agent consistently performed better than agents using alternate models (models that used dependency tree heuristics or human-like approaches to make sub-goal oriented choices), with an average performance advantage of 33.86% (with a standard deviation of 14.69%) over the best alternate agent. This shows that machine learning techniques can be consistently employed to make goal-oriented choices within an environment with recursive sub-goal dependencies and low amounts of pre-known information.
ContributorsKoleber, Derek (Author) / Acuna, Ruben (Thesis director) / Bansal, Ajay (Committee member) / W.P. Carey School of Business (Contributor) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Establishing a healthcare practice in the U. S. by a Mexican national involves many different steps at federal as well as state levels. The recent implementation of the Patient Protection and Affordable Care Act overhauls some requirements which include increased Medicaid eligibility as well as mandatory health insurance coverage. With these changes taking place over the next few years, the need for healthcare providers will expand. Consequently, I look into the requirements of establishing an urgent care practice in the state of Arizona. Given that Phoenix has a 40.8% Hispanic population and that the Affordable Care Act will increase the coverage of this demographic, it is the city of focus for my analysis. In order to make access to the Arizona healthcare market more impartial and accessible to Mexican entrepreneurs, changes need to be made to the certification process of medical physicians who graduated from Mexican universities. The general disadvantage of Mexican physicians as compared to their U. S. counterparts comes in the form of increased certification times and additional processes. An equal playing field will allow the ease in movement of medical physicians between the U. S. and Mexico which will help meet the increased demand over the next few years. From ownership to taxation and medical billing and coding, this analysis focuses on the many requirements needed to establish an urgent care in Arizona.
ContributorsIbarra, Joseph Anthony (Author) / Carlos, Velez-Ibanez (Thesis director) / Cruz-Torres, Maria (Committee member) / Barrett, The Honors College (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
Description
The primary purpose of this paper is to analyze urgent care centers and explain their role within the U.S. healthcare system. The introduction of urgent care into the market for health care services has brought with it a new way for consumers to receive non-emergent healthcare outside of traditional hours. Urgent care is often cited as a plausible alternative to care received at an emergency department or primary care physician's office. One of the key questions the author attempts to answer is: "To what degree are urgent care centers an economic substitute to emergency departments or physician's offices?" This paper looks at both projected demand from currently operating urgent care centers and consumer preference surveys to estimate the willingness of consumers to use urgent care. The method used to accomplish this task has been compiling scholarly research and data on urgent care centers. After a thorough examination of relevant studies and datasets, urgent care centers have been found to be just as preferred as emergency departments when considering non-emergent cases, specifically among individuals aged 18-44. The clear majority of consumers still prefer visiting a primary care physician over an urgent care center when it comes to episodic care, however. When taking into account wait times, differences in cost, and ease of access, urgent care becomes much more preferred than an emergency department and weakly preferred to a physician's office. There are still some concerns with urgent care, however. Questions of capacity to meet demand, access for underserved communities, and susceptibility to adverse selection have yet to be fully explored.
ContributorsBullington, Robert Heyburn (Author) / Foster, William (Thesis director) / Hill, John (Committee member) / Sandra Day O'Connor College of Law (Contributor) / W.P. Carey School of Business (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Abstract: The Ultimate Fighting Championship or UFC as it is commonly known, was founded in 1993 and has quickly built itself into the world's foremost authority on all things MMA (mixed martial arts) related. With pay-per-view and cable television deals in hand, the UFC has become a huge competitor in the sports market, rivaling the popularity of boxing for almost a decade. As with most other sports, the UFC has seen an influx of various analytics and data science over the past five to seven years. We see this revolution in football with the broadcast first down markers, basketball with tracking player movement, and baseball with locating pitches for strikes and balls, and now the UFC has partnered with statistics company Fightmetric, to provide in-depth statistical analysis of its fights. ESPN has their win probability metrics, and statistical predictive modeling has begun to spread throughout sports. All these stats were made to showcase the information about a fighter that one wouldn't typically know, giving insight into how the fight might go. But, can these fights be predicted? Based off of the research of prior individuals and combining the thought processes of relevant research into other sports leagues, I sought to use the arsenal of statistical analyses done by Fightmetric, along with the official UFC fighter database to answer the question of whether UFC fights could be predicted. Specifically, by using only data that would be known about a fighter prior to stepping into the cage, could I predict with any degree of certainty who was going to win the fight?
ContributorsMoorman, Taylor D. (Author) / Simon, Alan (Thesis director) / Simon, Phil (Committee member) / W.P. Carey School of Business (Contributor) / Department of Information Systems (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05