Classification: Absolutism vs Relativism
dc.contributor.author | Weist, Darren | |
dc.contributor.advisor | Farmer, Michael | |
dc.date.accessioned | 2017-01-11T16:55:23Z | |
dc.date.available | NO_RESTRICTION | en_US |
dc.date.available | 2017-01-11T16:55:23Z | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/135712 | |
dc.description.abstract | The thesis is organized in the following approach. First, we will address some of the main issues for general artificial intelligence. Second, to enhance our understanding of the problems, this article will provide a general overview of two axiological theories presented from philosophy: absolutism and relativism. We will discuss some examples of how these concepts relate to machine learning algorithms. Third, we will argue the thesis statement that classification requires relativism to be useful. The goal of this paper is to show how relativism can be used as a strategy to help solve some of the issues for general artificial intelligence. The concept of relativity can be useful for: (1) axiology, (2) defining things, and (3) memory. Then, the paper will conclude with future and final thoughts on the subject matter. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Absolutism | en_US |
dc.subject | artificial intelligence | en_US |
dc.subject | General Artificial Intelligence | en_US |
dc.subject | machine learning | en_US |
dc.subject | philosophy | en_US |
dc.subject | Relativism | en_US |
dc.subject.other | Artificial intelligence | en_US |
dc.subject.other | Computer science | en_US |
dc.subject.other | Philosophy | en_US |
dc.title | Classification: Absolutism vs Relativism | en_US |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | Master of Science (MS) | en_US |
dc.description.thesisdegreediscipline | Computer Science and Information Systems | en_US |
dc.description.thesisdegreegrantor | University of Michigan-Flint | en_US |
dc.contributor.committeemember | Wandmacher, Stevens | |
dc.identifier.uniqname | 63300506 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/135712/1/Weist2016.pdf | |
dc.description.filedescription | Description of Weist2016.pdf : Main article | |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.