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Hamilton-Jacobi-Bellman (HJB) equations arise as the dynamic programming equations of deterministic or stochastic optimal control problems. They allow to obtain the global optimum of these problems and to synthesize an optimal feedback control, leading to a solution robust against system perturbations. This is why, although HJB equations suffer from the curse of dimensionality, there remains an important effort for their numerical solution.
The aim of the workshop is to gather researchers who work on different numerical methods for HJB equations or more generally PDE, with the aim to bypass the curse of dimensionality or at least to improve complexity: max-plus or tropical, Monte Carlo, machine learning, fast marching, computational geometry.
The workshop will take place in Amphi Turing of bat. Sophie Germain of Paris Diderot University.
You can find the Programme here and the slides of the talks below.
Confirmed list of speakers:
Organizing and Scientific Committee: