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.

Bibliografische gegevens
Hoofdauteurs: Khan, Mahir Asaf, Ashraf, Adib, Amin, Tahmid Adib
Andere auteurs: Rashid, Warida
Formaat: Thesis
Taal:English
Gepubliceerd in: Brac University 2023
Onderwerpen:
Optimization landscape
Policy optimization
Deep reinforcement learning
Variance reduction
Control variates
Cognitive learning theory
Machine learning
Online toegang:http://hdl.handle.net/10361/18306

Internet

http://hdl.handle.net/10361/18306

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