Using reinforcement learning in 2D fighting games

A tétel rövid nézete
dc.contributor.advisorBogacsovics, Gergő
dc.contributor.authorMassoud, Hossam Ehab Adel
dc.contributor.departmentDE--Informatikai Kar
dc.date.accessioned2024-02-01T21:00:05Z
dc.date.available2024-02-01T21:00:05Z
dc.date.created2023-11-14
dc.description.abstractThis thesis explores the implementation of a reinforcement learning agent within a 2D fighting game environment utilizing Unity and its machine learning toolkit. The primary objective is to conduct a comprehensive comparative analysis between the reinforcement learning agent and a traditionally scripted artificial intelligence system. The evaluation aims to discern the extent to which the integration of a reinforcement learning agent enhances the overall player experience within the gaming environment. Additionally, this research delves into the intricate process of creating the game itself, providing insights into the development challenges encountered throughout the project's lifecycle. By scrutinizing both the technical aspects of reinforcement learning in a gaming context and the practical hurdles faced during game creation, this thesis contributes valuable perspectives to the intersection of artificial intelligence, game design, and player engagement.
dc.description.courseProgramtervező informatikus
dc.description.degreeBSc/BA
dc.format.extent41
dc.identifier.urihttps://hdl.handle.net/2437/365912
dc.language.isoen
dc.rights.accessHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectUnity
dc.subjectVideo game development
dc.subjectreinforcement learning
dc.subject.dspaceDEENK Témalista::Informatika::Információtechnológia
dc.titleUsing reinforcement learning in 2D fighting games
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