Searching for anomalies with multiple plays under delay and switching costs

Tidhar Lambez, Kobi Cohen

Research output: Contribution to journalConference articlepeer-review


— The problem of searching for L anomalous processes among M processes is considered. At each time, the decision maker can observe a subset of K processes (i.e., multiple plays). The measurement drawn when observing a process follows one of two different distributions, depending whether the process is normal or abnormal. The goal is to design a policy that minimizes the Bayes risk which balances between the sample complexity, detection errors, and the switching cost associated with switching across processes. We develop a policy, dubbed consecutive controlled sensing (CCS), to achieve this goal. We prove theoretically that CCS is asymptotically optimal in terms of minimizing the Bayes risk as the sample complexity approaches infinity. Simulation results demonstrate strong performance of CCS in the finite regime as well.

Original languageEnglish
Pages (from-to)4975-4979
Number of pages5
JournalProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
StatePublished - 1 Jan 2021
Event2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Virtual, Toronto, Canada
Duration: 6 Jun 202111 Jun 2021


  • Active hypothesis testing
  • Anomaly detection
  • Controlled sensing
  • Sequential design of experiments

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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