dc.creator | Bub, Cassandra | |
dc.date.accessioned | 2017-10-10T20:32:28Z | |
dc.date.available | 2017-10-10T20:32:28Z | |
dc.date.created | 2018-05 | |
dc.date.submitted | May 2018 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/164579 | |
dc.description.abstract | In this paper, we look at the performance of a time-delay neural network in a scenario requiring memory as well as reactivity. Utilizing a ball catching scenario where the agent will have to move to catch a falling ball, and then remembering where the second one was relative to its position in order to catch the second, we can determine how the time-delay neural networks perform in these tasks. For comparison to previous work with this scenario, we will compare the performance to a feed-forward network and a recurrent neural network. | en |
dc.format.mimetype | application/pdf | |
dc.subject | neural networks | en |
dc.subject | artificial intelligence | en |
dc.subject | neuroscience | en |
dc.subject | computer science | en |
dc.subject | genetic algortihms | en |
dc.title | Analysis of Time-Delay Artificial Neural Networks in Ball Catching Task | en |
dc.type | Thesis | en |
thesis.degree.department | Computer Science & Engineering | en |
thesis.degree.discipline | Computer Science | en |
thesis.degree.grantor | Undergraduate Research Scholars Program | en |
thesis.degree.name | BS | en |
thesis.degree.level | Undergraduate | en |
dc.contributor.committeeMember | Choe, Yoonsuck | |
dc.type.material | text | en |
dc.date.updated | 2017-10-10T20:32:28Z | |