Weak adaptive submodularity and group-based active diagnosis with applications to state estimation with persistent sensor faults

Sze Yong, Lingyun Gao, Necmiye Ozay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we consider adaptive decision-making problems for stochastic state estimation with partial observations. First, we introduce the concept of weak adaptive submodularity, a generalization of adaptive submodularity, which has found great success in solving challenging adaptive state estimation problems. Then, for the problem of active diagnosis, i.e., discrete state estimation via active sensing, we show that an adaptive greedy policy has a near-optimal performance guarantee when the reward function possesses this property. We further show that the reward function for group-based active diagnosis, which arises in applications such as medical diagnosis and state estimation with persistent sensor faults, is also weakly adaptive submodular. Finally, in experiments of state estimation for an aircraft electrical system with persistent sensor faults, we observe that an adaptive greedy policy performs equally well as an exhaustive search.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2574-2581
Number of pages8
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Other

Other2017 American Control Conference, ACC 2017
CountryUnited States
CitySeattle
Period5/24/175/26/17

Fingerprint

State estimation
Sensors
Decision making
Experiments

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Yong, S., Gao, L., & Ozay, N. (2017). Weak adaptive submodularity and group-based active diagnosis with applications to state estimation with persistent sensor faults. In 2017 American Control Conference, ACC 2017 (pp. 2574-2581). [7963340] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2017.7963340

Weak adaptive submodularity and group-based active diagnosis with applications to state estimation with persistent sensor faults. / Yong, Sze; Gao, Lingyun; Ozay, Necmiye.

2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2574-2581 7963340.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yong, S, Gao, L & Ozay, N 2017, Weak adaptive submodularity and group-based active diagnosis with applications to state estimation with persistent sensor faults. in 2017 American Control Conference, ACC 2017., 7963340, Institute of Electrical and Electronics Engineers Inc., pp. 2574-2581, 2017 American Control Conference, ACC 2017, Seattle, United States, 5/24/17. https://doi.org/10.23919/ACC.2017.7963340
Yong S, Gao L, Ozay N. Weak adaptive submodularity and group-based active diagnosis with applications to state estimation with persistent sensor faults. In 2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2574-2581. 7963340 https://doi.org/10.23919/ACC.2017.7963340
Yong, Sze ; Gao, Lingyun ; Ozay, Necmiye. / Weak adaptive submodularity and group-based active diagnosis with applications to state estimation with persistent sensor faults. 2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2574-2581
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