20.500.12556/DKUM-36637 SAMOOJAČITVENO UČENJE REINFORCEMENT LEARNING V diplomskem delu predstavljamo samoojačitveno učenje, ki je področje strojnega učenja in se ukvarja z vprašanjem, kako naj agent deluje v okolju, da doseže čim večjo nagrado. V nalogi opravimo splošen pregled te teme, nato podrobneje opišemo nekaj pomembnejših metod, eno izmed njih pa implementiramo v mrežnem okolju lovec-plen. Na koncu predstavimo še naš program ter analiziramo dobljene rezultate. In this diploma work we present reinforcement learning, which is an area of machine learning that studies the question of how an agent ought to act in an environment to achieve maximum reward. In this work we take a general look at the topic, then describe a few of the more important methods in detail and implement one of them in the predator-prey grid world domain. In the end, we present our program and analyze its results. strojno učenje nenadzorovano učenje mrežno okolje lovec-plen machine learning unsupervised learning predator-prey grid world true true false [M. Mlakar] Slovenski jezik Angleški jezik Diplomsko delo/naloga 2012-06-18 16:39:01 2012-07-11 09:56:20 2022-04-21 14:21:19 2021-04-15 03:47:51 2012 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.89:004.4(043.2) 16232214 URN:SI:UM:DK:KU334R2T UNI_Mlakar_Matej_2012.pdf UNI_Mlakar_Matej_2012.pdf 1 1B2A4260CAD8EE7A2072F6E21619AE90 e16eaf16edd4699f2ed89b656855edc09a626ac1bb037ce521f92b3cabb7af3b 19254396-7c08-11eb-bb7a-00155d0001ca 20.500.12556/dkum/e00e27d0-f18d-4ddb-b3a6-34e2e97fa37c https://dk.um.si/Dokument.php?lang=slv&id=47901 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0