Exploring Evolution Strategies for Reinforcement Learning in the Obstacle Tower Environment

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics

Detalhes bibliográficos
Autor principal: Kuypers, Julian (author)
Formato: masterThesis
Idioma:eng
Publicado em: 2021
Assuntos:
deep reinforcement learning
evolution strategies
genetic algorithm
obstacle Tower
obstacle Tower Challenge
unity
neuroevolution
reinforcement learning benchmark.
Texto completo:http://hdl.handle.net/10362/127522
País:Portugal
Oai:oai:run.unl.pt:10362/127522

Texto Completo

http://hdl.handle.net/10362/127522

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