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Frederik Kelbel's Projects

gpandga icon gpandga

GP/GA-algorithm for prime-number generation

iaml2018 icon iaml2018

Introductory Applied Machine Learning [Labs & CourseWork]

optimal-control-of-agent-based-dynamics icon optimal-control-of-agent-based-dynamics

Ever since the concepts of dynamic programming wereintroduced, one of the most difficult challenges has been to adequatelyaddress high-dimensional control problems. With growing dimension-ality, the utilisation of Deep Neural Networks promises to circumventthe issue of an otherwise exponentially increasing complexity. Thepaper specifically investigates the sampling issues the Deep GalerkinMethod is subjected to. It proposes a drift relaxation-based samplingapproach to alleviate the symptoms of high-variance policy approxi-mations. This is validated on mean-field control problems; namely, thevariations of the opinion dynamics presented by the Sznajd and theHegselmann-Krause model. The resulting policies induce a significantcost reduction over manually optimised control functions and show improvements on the Linear-Quadratic Regulator problem over the Deep FBSDE approach.

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