Non-adaptative Policies for 20 Questions Target Localization
نویسندگان
چکیده
The problem of the target localization with noise is considered. The target is a sample from a continuous random variable with known distribution and the goal is to locate this target with minimum mean squared error. The localization scheme or policy proceeds by queries, or questions, weather or not the target belongs to some subset as it is addressed in the 20-question framework. These subsets are not constrained to be intervals and the answers to the queries are noisy. While this situation is well studied for adaptive querying, we concentrate in this paper on non adaptive querying policies. We consider policies based on the dyadic questions. We calculate the asymptotic minimum achievable distortion under such policies. Furthermore, we exhibit a policy name the Aurelian achieving this bound.
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