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Dynamic search under false alarms

We consider the dynamic search of a target located in one of K cells. At each time, one cell is searched, and the search result is subject to false alarms. The objective is a policy that governs the sequential selection of the cells to minimize the error probability of detecting the whereabouts of the target within a fixed time horizon. We show that the optimal search policy is myopic in nature with a simple structure. The result finds applications in statistical fraud detection, anomaly localization, and target search.