Minimal Exploration in Episodic Reinforcement Learning

Minimal Exploration in Episodic Reinforcement Learning

Exploration-exploitation trade-off is a fundamental dilemma that reinforcement learning algorithms face. This dilemma is also central to the design of various state of the art bandit algorithms. We take inspiration from these algorithms and try to design reinforcement learning algorithms in an episo...

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Bibliographic Details
Main Author: Tripathi, Ardhendu Shekhar
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2018
Subjects:
Reinforcemebt Learning
Exploitation
Exploration
Regret
Optimism in Face of Uncertainty
Bayesian
Engineering and Technology
Teknik och teknologier
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233579

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233579

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