Performance of bandit methods in acoustic relay positioning
Name
Mei Cheung acc2014_final.pdf
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Author(s)
Cheung, Mei Yi
Leighton, Joshua C.
Mitra, Urbashi
Singh, Hanumant
Hover, Franz S.
Date Issued
June 2014
Journal
Proceedings of the 2014 American Control Conference
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Cheung, Mei Yi, Joshua Leighton, Urbashi Mitra, Hanumant Singh, and Franz S. Hover. “Performance of Bandit Methods in Acoustic Relay Positioning.” 2014 American Control Conference (June 2014).
Version
Author's final manuscript
Abstract
We consider the problem of maximizing underwater acoustic data transmission, by adaptively positioning a mobile relay. This is a classic exploration vs. exploitation scenario well-described by a multi-armed bandit formulation, which in its canonical form is optimally solved by the Gittins index rule. For an ocean vehicle traveling between distant waypoints, however, switching costs are significant, and the MAB with switching costs has no optimal index policy. To address this we have developed a strong adaptation of the Gittins index rule that employs limited-horizon enumeration. We describe autonomous shallow-water field experiments conducted in the Charles River (Boston, MA) with unmanned vehicles and acoustic modems, and compare the performance of different algorithms. Our switching-costs-aware MAB heuristic offers both superior real-time performance in decision-making and efficient learning of the unknown field.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/ACC.2014.6859385
