Title:
Training Artificial Intelligence
Training Artificial Intelligence
| dc.contributor.advisor | Isbell, Charles L. | |
| dc.contributor.author | Gasser, Tarik | |
| dc.contributor.committeeMember | Howard, Ayanna | |
| dc.contributor.department | Computer Science | |
| dc.date.accessioned | 2021-06-30T17:37:23Z | |
| dc.date.available | 2021-06-30T17:37:23Z | |
| dc.date.created | 2020-12 | |
| dc.date.issued | 2020-12 | |
| dc.date.submitted | December 2020 | |
| dc.date.updated | 2021-06-30T17:37:23Z | |
| dc.description.abstract | Training an Artificial Intelligence could be challenging in so many ways. In our research we are building a strong AI that has the ability to make decision on its own without given explicit answers. We are using Reinforcement learning with Imitating learning to train the Artificial Intelligent offline before putting him through the environment. | |
| dc.description.degree | Undergraduate | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/64849 | |
| dc.language.iso | en_US | |
| dc.publisher | Georgia Institute of Technology | |
| dc.subject | Artificial Intelligence | |
| dc.subject | Environment | |
| dc.subject | Imitation leaning | |
| dc.subject | StrongAI | |
| dc.subject | Reinforcement learning | |
| dc.title | Training Artificial Intelligence | |
| dc.type | Text | |
| dc.type.genre | Undergraduate Thesis | |
| dspace.entity.type | Publication | |
| local.contributor.advisor | Isbell, Charles L. | |
| local.contributor.corporatename | College of Computing | |
| local.contributor.corporatename | School of Computer Science | |
| local.contributor.corporatename | Undergraduate Research Opportunities Program | |
| local.relation.ispartofseries | Undergraduate Research Option Theses | |
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| thesis.degree.level | Undergraduate |