Sampling Based Approaches for Minimizing Regret in Uncertain Markov Decision Processes (MDPs)

Sampling Based Approaches for Minimizing Regret in Uncertain Markov Decision Processes (MDPs)

© 2017 AI Access Foundation. All rights reserved. Markov Decision Processes (MDPs) are an effective model to represent decision processes in the presence of transitional uncertainty and reward tradeoffs. However, due to the difficulty in exactly specifying the transition and reward functions in MDPs...

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Bibliographic Details
Main Authors: Ahmed, Asrar, Varakantham, Pradeep, Lowalekar, Meghna, Adulyasak, Yossiri, Jaillet, Patrick
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: AI Access Foundation 2021
Online Access:https://hdl.handle.net/1721.1/136337

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https://hdl.handle.net/1721.1/136337

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