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Computation of suboptimal randomized strategies for steering the random motion of a point under partial observation

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Abstract

Consider the random motion in the plane of a pointM, whose velocityv=(v 1,v 2) is perturbed by an ℝ2-valued Gaussian white noise. Only noisy nonlinear observations taken on the point location (state) are available toM. The velocityv is of the formv(y)=∭ u (u 1,u 2 y (du), wherey denotes the value of the observed signal,U is the range of the velocity, and, for eachy, μ y is a probability measure on ℬ(U). Using the available observations, the pointM wishes to steer itself into a given target set by choosing a randomized strategy μ={μ y :y ∈ ∝2}. Sufficient conditions on weak optimal randomized strategies are derived. An algorithm for computing weak suboptimal randomized strategies is suggested, and the strategies are computed for a variety of cases.

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Communicated by G. Leitmann

This work was partially supported by a grant from Control Data.

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Yavin, Y. Computation of suboptimal randomized strategies for steering the random motion of a point under partial observation. J Optim Theory Appl 44, 159–179 (1984). https://doi.org/10.1007/BF00934899

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