Abstract
We consider a variation of upper confidence bound strategy for multi-armed bandit in batch processing setting. Invariant descriptions with the unit control horizon are obtained for upper bounds in the strategy and for regret. A set of Monte-Carlo simulations are performed for different settings of MABs to determine the minimax regret for multi-armed bandits with different configurations.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.