Matching Items (3)
Filtering by
- All Subjects: Mathematics
Description
Analytic research on basketball games is growing quickly, specifically in the National Basketball Association. This paper explored the development of this analytic research and discovered that there has been a focus on individual player metrics and a dearth of quantitative team characterizations and evaluations. Consequently, this paper continued the exploratory research of Fewell and Armbruster's "Basketball teams as strategic networks" (2012), which modeled basketball teams as networks and used metrics to characterize team strategy in the NBA's 2010 playoffs. Individual players and outcomes were nodes and passes and actions were the links. This paper used data that was recorded from playoff games of the two 2012 NBA finalists: the Miami Heat and the Oklahoma City Thunder. The same metrics that Fewell and Armbruster used were explained, then calculated using this data. The offensive networks of these two teams during the playoffs were analyzed and interpreted by using other data and qualitative characterization of the teams' strategies; the paper found that the calculated metrics largely matched with our qualitative characterizations of the teams. The validity of the metrics in this paper and Fewell and Armbruster's paper was then discussed, and modeling basketball teams as multiple-order Markov chains rather than as networks was explored.
ContributorsMohanraj, Hariharan (Co-author) / Choi, David (Co-author) / Armbruster, Dieter (Thesis director) / Fewell, Jennifer (Committee member) / Brooks, Daniel (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-05
Description
Pogonomyrmex californicus (a species of harvester ant) colonies typically have anywhere from one to five queens. A queen can control the ratio of female to male offspring she produces, field research indicating that this ratio is genetically hardwired and does not change over time relative to other queens. Further, a queen has an individual reproductive advantage if she has a small reproductive ratio. A colony, however, has a reproductive advantage if it has queens with large ratios, as these queens produce many female workers to further colony success. We have developed an agent-based model to analyze the "cheating" phenotype observed in field research, in which queens extend their lifespans by producing disproportionately many male offspring. The model generates phenotypes and simulates years of reproductive cycles. The results allow us to examine the surviving phenotypes and determine conditions under which a cheating phenotype has an evolutionary advantage. Conditions generating a bimodal steady state solution would indicate a cheating phenotype's ability to invade a cooperative population.
ContributorsEngel, Lauren Marie Agnes (Author) / Armbruster, Dieter (Thesis director) / Fewell, Jennifer (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Division of Labor among social insects is frequently discussed in regards to the colony's worker population. However, before a colony achieves a worker population, a queen is required to perform all of the tasks necessary for her survival: foraging, building the colony, and brood care. A simple ODE model was developed through the use of a framework of replicator equations in dynamical environments to investigate how queen ants perform and distribute all of the tasks necessary for her and her colony's survival by incorporating individual internal thresholds and environmental stimulus. Modi�cations to the internal threshold, risk of performing the task, and the rate of increase of the environmental stimulus were also explored. Because of the simplicity of the model, it could also be used to measure the task performance of larger populations of social insects. However, the model has only been applied to the data collected from Pogonomyrmex barbatus single queen ants.
ContributorsKincade, Katherine Margaret (Author) / Kang, Yun (Thesis director) / Fewell, Jennifer (Committee member) / Lanchier, Nicolas (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12