Análisis de dos algoritmos de Reinforcement Learning aplicados a OpenAi Gym Retro

dc.contributorTakahashi Rodríguez, Silvia
dc.contributorTakahashi Rodríguez, Silvia
dc.creatorGonzález Oviedo, Rodrigo José
dc.date.accessioned2023-08-16T13:44:18Z
dc.date.accessioned2023-09-07T01:27:49Z
dc.date.available2023-08-16T13:44:18Z
dc.date.available2023-09-07T01:27:49Z
dc.date.created2023-08-16T13:44:18Z
dc.date.issued2023-08-15
dc.identifierhttp://hdl.handle.net/1992/69749
dc.identifierinstname:Universidad de los Andes
dc.identifierreponame:Repositorio Institucional Séneca
dc.identifierrepourl:https://repositorio.uniandes.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8728383
dc.description.abstractEl presente trabajo explica detalladamente el funcionamiento de los algoritmos de aprendizaje reforzado, DQN y PPO. Adicionalmente se realiza una comparación entre estos algoritmos utilizando el framework de OpenAI Gym-retro, para entrenar un game agent basado en cada uno de los algoritmos.
dc.languagespa
dc.publisherUniversidad de los Andes
dc.publisherIngeniería de Sistemas y Computación
dc.publisherFacultad de Ingeniería
dc.publisherDepartamento de Ingeniería Sistemas y Computación
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dc.rightsAtribución 4.0 Internacional
dc.rightshttp://creativecommons.org/licenses/by/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.titleAnálisis de dos algoritmos de Reinforcement Learning aplicados a OpenAi Gym Retro
dc.typeTrabajo de grado - Pregrado


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