Playing a 3D Tunnel Game Using Reinforcement Learning
Hraní 3D tunelové hry pomocí zpětnovazebního učení
bakalářská práce (OBHÁJENO)
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Trvalý odkaz
http://hdl.handle.net/20.500.11956/183062Identifikátory
SIS: 258804
Kolekce
- Kvalifikační práce [11199]
Autor
Vedoucí práce
Oponent práce
Straka, Milan
Fakulta / součást
Matematicko-fyzikální fakulta
Obor
Computer Science with specialisation in Artificial Intelligence
Katedra / ústav / klinika
Katedra softwaru a výuky informatiky
Datum obhajoby
29. 6. 2023
Nakladatel
Univerzita Karlova, Matematicko-fyzikální fakultaJazyk
Angličtina
Známka
Výborně
Klíčová slova (česky)
tunnel game|reinforcement learning|artificial intelligence|algorithmsKlíčová slova (anglicky)
tunnel game|reinforcement learning|artificial intelligence|algorithmsTunnel games are a type of 3D video game in which the player moves through a tunnel and tries to avoid obstacles by rotating around the axis of the tunnel. These games often involve fast-paced gameplay and require quick reflexes and spatial awareness to navigate through the tunnel successfully. The aim of this thesis is to explore the representation of a tunnel game in a discrete manner and to compare various reinforcement learning algorithms in this context. The objective is to evaluate the performance of these algorithms in a game setting and identify potential strengths and limitations. The results of this study may offer insights on the application of discrete tabular methods in the development of AI agents for other continuous games.