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.

Bibliografski detalji
Glavni autori: Khan, Mahir Asaf, Ashraf, Adib, Amin, Tahmid Adib
Daljnji autori: Rashid, Warida
Format: Disertacija
Jezik:English
Izdano: Brac University 2023
Teme:
Optimization landscape
Policy optimization
Deep reinforcement learning
Variance reduction
Control variates
Cognitive learning theory
Machine learning
Online pristup:http://hdl.handle.net/10361/18306

Internet

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

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