Gradient-based Deep Reinforcement Learning
dc.contributor | Aalto-yliopisto | fi |
dc.contributor | Aalto University | en |
dc.contributor.advisor | Jung, Alexander | |
dc.contributor.author | Afteniy, Maxim | |
dc.contributor.department | Tietotekniikan laitos | fi |
dc.contributor.school | Perustieteiden korkeakoulu | fi |
dc.contributor.supervisor | Kannala, Juho | |
dc.date.accessioned | 2018-06-05T12:22:13Z | |
dc.date.available | 2018-06-05T12:22:13Z | |
dc.date.issued | 2018-04-26 | |
dc.format.extent | 25 | |
dc.format.mimetype | application/pdf | en |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/31817 | |
dc.identifier.urn | URN:NBN:fi:aalto-201806053240 | |
dc.language.iso | en | en |
dc.programme | Tietotekniikka TIK | fi |
dc.programme.major | Tietotekniikka | fi |
dc.programme.mcode | SCI3027 | fi |
dc.subject.keyword | reinfrocement learning | en |
dc.subject.keyword | deep reinforcement learning | en |
dc.subject.keyword | machine learning | en |
dc.subject.keyword | Q-learning | en |
dc.subject.keyword | deep Q-learning | en |
dc.subject.keyword | optimal control | en |
dc.title | Gradient-based Deep Reinforcement Learning | en |
dc.type | G1 Kandidaatintyö | fi |
dc.type.dcmitype | text | en |
dc.type.ontasot | Bachelor's thesis | en |
dc.type.ontasot | Kandidaatintyö | fi |