Seminari - Dipartimento Computer Science Seminari - Dipartimento Computer Science validi dal 02.12.2022 al 02.12.2023. https://www.di.univr.it/?ent=seminario&rss=0&lang=en Data-driven methods for optimal control https://www.di.univr.it/?ent=seminario&rss=0&lang=en&id=5798 Relatore: Dante Kalise; Provenienza: Imperial College London; Data inizio: 2022-12-02; Ora inizio: 8.45; Referente interno: Giacomo Albi; Riassunto: In this short course, we will study how to incorporate elements of machine learning into optimal control design. The course is split into 3 parts: 1 Fundamentals of optimal control: dynamic optimization, linear-quadratic control, dynamic programming and Pontryagin#39;s maximum principle. Nonlinear optimal control. 2 Approximation methods in high dimensions: polynomial approximation, deep neural networks. Optimization techniques: LASSO regression, stochastic gradient descent, training neural networks. 3 Synthetic data-driven schemes for optimal control. Combining the first two parts, we will study the construction of data-driven schemes for the approximation of high-dimensional nonlinear control laws. Examples in Matlab. The schedule of the course is: Friday 02/12 9:00. - 10:30, room C Monday 05/12 9:00. - 10:30, room G Tuesday 06/12 10:30 - 12:30 Sala riunioni secondo piano Students interested are invited to contact Prof. Albi (giacomo.albi@univr.it) . Fri, 2 Dec 2022 08:45:00 +0100 https://www.di.univr.it/?ent=seminario&rss=0&lang=en&id=5798