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ICRA
2007
IEEE

A Decision-Making Framework for Control Strategies in Probabilistic Search

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A Decision-Making Framework for Control Strategies in Probabilistic Search
Abstract— This paper presents the search problem formulated as a decision problem, where the searcher decides whether the target is present in the search region, and if so, where it is located. Such decision-based search tasks are relevant to many research areas, including mobile robot missions, visual search and attention, and event detection in sensor networks. The effect of control strategies in search problems on decisionmaking quantities, namely time-to-decision, is investigated in this work. We present a Bayesian framework in which the objective is to improve the decision, rather than the sensing, using different control policies. Furthermore, derivations of closed-form expressions governing the evolution of the belief function are also presented. As this framework enables the study and comparison of the role of control for decision-making applications, the derived theoretical results provide greater insight into the sequential processing of decisions. Numerical studies are pre...
Timothy H. Chung, Joel W. Burdick
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ICRA
Authors Timothy H. Chung, Joel W. Burdick
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