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.

Bibliografiska uppgifter
Huvudupphovsmän: Khan, Mahir Asaf, Ashraf, Adib, Amin, Tahmid Adib
Övriga upphovsmän: Rashid, Warida
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2023
Ämnen:
Optimization landscape
Policy optimization
Deep reinforcement learning
Variance reduction
Control variates
Cognitive learning theory
Machine learning
Länkar:http://hdl.handle.net/10361/18306

Internet

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

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