Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/24316
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dc.contributor.authorBouzegzeg, Mohamed El Mahdi-
dc.contributor.authorDellali, Mohamed Fethi-
dc.date.accessioned2023-05-29T08:37:53Z-
dc.date.available2023-05-29T08:37:53Z-
dc.date.issued2022-
dc.identifier.urihttps://di.univ-blida.dz/jspui/handle/123456789/24316-
dc.description88 p ; illustrfr_FR
dc.description.abstractA well-thought-out strategy was followed in order to achieve the project's stated objective, which is to use Reinforcement learning and Unity game engine to create an autonomous parking simulation. This strategy started with a discussion of various artificial intelligence (AI) subsets and their methods, followed by a detailed discussion of reinforcement learning, Unity game engine, and ML-Agents. Finally, we created a simulation using Unity game engine that included a parking lot as “the environment” and a car as “the agent”, and then we used reinforcement learning and ML-Agents to train the car to park autonomouslyfr_FR
dc.language.isoenfr_FR
dc.publisherUniv Blida1fr_FR
dc.titleAutonomous Parking Simulation using Unity Game Engine and Reinforcement Learningfr_FR
Appears in Collections:Mémoires de Master

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