Adaptive Sensor Placement for Continuous Spaces

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Adaptive Sensor Placement for Continuous Spaces

June 9 - 15 2019 ICML, Long Beach, USA

Authors: James Grant (PROWLER.io and Lancaster University), Alexis Boukouvalas,
Ryan-Rhys Griffiths (Prowler.io and University of Cambridge), David
Leslie (Prowler.io and Lancaster University), Sattar Vakili and Enrique
Munoz De Cote

Abstract: Repeatedly placing sensors along an interval (in time or space) to detect as many events as possible. Each replacement opportunity needs to balance exploration (finding out information for future deployments) and exploitation (detecting events in the current deployment). The difference from standard bandit papers is that the actions are intervals. There are obvious generalisations to selecting regions instead of intervals.

Multi-agent Systems

Statistical Learning Theory

Sequential Decision-Making

Poisson Process


See paper

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