Multiple-Experiment Quickest Change Detection under Cost Constraints

Lubenia, Patrick Vincent N.; Banerjee, Taposh

Permalink

https://hdl.handle.net/2142/130302 Copy

Description

Title

Multiple-Experiment Quickest Change Detection under Cost Constraints

Author(s)

• Lubenia, Patrick Vincent N.
• Banerjee, Taposh

Issue Date

2025-09-17

Keyword(s)

• Controlled sensing
• CUSUM
• Data-efficient
• Experiment design
• Multiple-experiment
• Quickest change detection
• Sampling control

Abstract

In the classical quickest change detection problem, an observer performs only one experiment to monitor a stochastic process. This paper considers the case where, at each observation time, the decision-maker needs to choose between multiple experiments with different information qualities and costs. The goal is to minimize the worst-case average detection delay subject to false alarm and cost constraints. An algorithm called the 2E-CUSUM algorithm is developed to achieve this goal for the two-experiment case. Multiple-experiment designs are also studied, and the 2E-CUSUM algorithm is extended accordingly. The proposed algorithms are shown to be asymptotically optimal.

Publisher

Allerton Conference on Communication, Control, and Computing

Series/Report Name or Number

2025 61st Allerton Conference on Communication, Control, and Computing Proceedings

ISSN

2836-4503

Type of Resource

Text

Genre of Resource

Conference Paper/Presentation

Language

eng

Handle URL

https://hdl.handle.net/2142/130302&&

Copyright and License Information

Copyright 2025 is held by Patrick Vincent N. Lubenia and Taposh Banerjee.

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