Analyzing optimization landscape of recent policy optimization methods in deep RL

Analyzing optimization landscape of recent policy optimization methods in deep RL

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Dades bibliogràfiques
Autors principals:	Khan, Mahir Asaf, Ashraf, Adib, Amin, Tahmid Adib
Altres autors:	Rashid, Warida
Format:	Thesis
Idioma:	English
Publicat:	Brac University 2023
Matèries:	Optimization landscape Policy optimization Deep reinforcement learning Variance reduction Control variates Cognitive learning theory Machine learning
Accés en línia:	http://hdl.handle.net/10361/18306

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