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Chaouach, L. (author), Boskos, D. (author), Oomen, T.A.E. (author)Ambiguity sets of probability distributions are a prominent tool to hedge against distributional uncertainty in stochastic optimization. The aim of this paper is to build tight Wasserstein ambiguity sets for data-driven optimization problems. The method exploits independence between the distribution components to introduce structure in the...conference paper 2022
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Franci, B. (author), Grammatico, S. (author)We consider the stochastic generalized Nash equilibrium problem (SGNEP) with expected-value cost functions. Inspired by Yi and Pavel (2019), we propose a distributed generalized Nash equilibrium seeking algorithm based on the preconditioned forward-backward operator splitting for SGNEPs, where, at each iteration, the expected value of the...journal article 2021
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Kolekar, S.B. (author), de Winter, J.C.F. (author), Abbink, D.A. (author)The interaction between a human driver and an automated driving system may improve when the automation is designed in such a way that it behaves in a human-like manner. This paper introduces a human-like steering model, in which the driver adapts to the risk due to uncertainty in the environment. Current steering models take a risk-neutral...conference paper 2017