dc.contributor.advisor | Bremdal, Bernt Arild | |
dc.contributor.author | Granmo, Gisle Jaran | |
dc.date.accessioned | 2021-12-06T08:56:14Z | |
dc.date.available | 2021-12-06T08:56:14Z | |
dc.date.issued | 2021-05-18 | en |
dc.description.abstract | This thesis will explore interaction between non-supervised machinelearning agents, with a focus on traffic situations. We intend to showthat self-interested agents can arrive at mutually beneficial strategiesaccording to general game theory, achieving pure or mixed Nash equi-libria, and that this has practical applications for unmanned vehicles.We will start by verifying against simple one stage models, specifi-cally “battle of the sexes” and “chicken race”, before extending this touncontrolled four way intersections. | en_US |
dc.identifier.uri | https://hdl.handle.net/10037/23273 | |
dc.language.iso | eng | en_US |
dc.publisher | UiT Norges arktiske universitet | no |
dc.publisher | UiT The Arctic University of Norway | en |
dc.rights.holder | Copyright 2021 The Author(s) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/4.0 | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | en_US |
dc.subject.courseID | DTE-3900 | |
dc.subject | VDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 422 | en_US |
dc.subject | VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Algoritmer og beregnbarhetsteori: 422 | en_US |
dc.title | Learning social codes for self-interested agents | en_US |
dc.type | Master thesis | en |
dc.type | Mastergradsoppgave | no |