Evaluating the application of Reinforcement Learning algorithms on video games
dc.contributor.advisor1 | Malheiros, Marcelo De Gomensoro | |
dc.contributor.advisor1Lattes | http://lattes.cnpq.br/3846222742415187 | pt_BR |
dc.creator | Vian, Leandro | |
dc.date.accessioned | 2018-12-27T19:42:30Z | |
dc.date.available | 2018-12-27T19:42:30Z | |
dc.date.issued | 2018-10-08 | |
dc.date.submitted | 2018-07-11 | |
dc.description.abstract | Artificial Intelligence has become part of our everyday for quite some time now: movies have portrayed it in its histories, news have reported of its advancements and we have seen its results in our electronics and machinery. In the latest years a new term started to gain traction, Machine Learning, with many articles, companies and media covering it, opening possibilities of what could be achieved with the ability to train computers using all the data generated nowadays. This work gives an overview of a few current Machine Learning techniques, aiming in the application of automated video game playing. In particular, it uses the Starcraft II Reinforcement Environment as a testbed for evaluating the selected automated learning strategies. | pt_BR |
dc.identifier.citation | VIAN, Leandro. Evaluating the application of Reinforcement Learning algorithms on video games. 2018. Monografia (Graduação em Engenharia de Software) – Universidade do Vale do Taquari - Univates, Lajeado, 11 jul. 2018. Disponível em: http://hdl.handle.net/10737/2229. | pt_BR |
dc.identifier.uri | http://hdl.handle.net/10737/2229 | |
dc.language.iso | en | pt_BR |
dc.rights | openAccess | pt_BR |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Artificial Intelligence | pt_BR |
dc.subject | Machine Learning | pt_BR |
dc.subject | neural networks | pt_BR |
dc.subject | Reinforcement Learning | pt_BR |
dc.subject | Starcraft II | pt_BR |
dc.subject.cnpq | ENG | pt_BR |
dc.title | Evaluating the application of Reinforcement Learning algorithms on video games | pt_BR |
dc.type | bachelorThesis | pt_BR |