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<h2 style="font-size:1.2em;">Seminario de Probabilidad y Estadística</h2>
<h3 style="font-size:1em;">Título: <em>Optimal Control of Stochastic Systems with Partial Information</em></h3>
<h3 style="font-size:1em;">Expositor: Raul Tempone <span style="font-weight:400;">(Alexander von Humboldt Professor RWTH-Aachen & KAUST)</span></h3>
<div style="font-size:1em!important;"><p><b>Resumen: </b><span>This work presents a control framework for continuous-time stochastic optimal control problems with</span><br/><span>discrete-time, partial, noisy, and potentially controllable measurements. The approach uses a probability</span><br/><span>measure-valued state and Bayesian updates to incorporate noisy data into control decisions. Control</span><br/><span>optimality is characterized by interlaced Hamilton-Jacobi-Bellman (HJB) equations with controlled</span><br/><span>impulse steps at measurement times. For Gaussian-controlled processes, an equivalent finite-dimensional</span><br/><span>HJB equation based on the state’s mean and covariance is derived. Numerical examples demonstrate the</span><br/><span>method’s effectiveness under perfect, none, and noisy (possibly controllable) observations, highlighting the</span><br/><span>impact of observation uncertainty on control strategies and performance.</span></p></div>
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<p style="font-size:1em;"><b>Viernes 4/7 a las 10:30</b><br>
<b>salón 703 de FING.</b>
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<p style="font-size:1em;"><b>Contacto: </b>Alejandro Cholaquidis - <a href="mailto:acholaquidis@hotmail.com">acholaquidis@hotmail.com</a></p>
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<p><span>https://salavirtual-udelar.zoom.us/j/87951133501?pwd=aUZGIzluqNSQNDCYQFRT5rESb9aItr.1</span></p><hr>
Más seminarios en: <a href="http://www.cmat.edu.uy/seminarios">http://www.cmat.edu.uy/seminarios</a>
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