Abstract: In this article, we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems ...
Abstract: We explored the application of Risk-averse Reinforcement Learning (Risk-averse RL) in Constrained Markov Decision Process (CMDP) in optimizing investment portfolios, incorporating ...
1 Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, Luxembourg 2 Department of Electrical and Computer Engineering (EIT), RPTU University of ...
We are considering the NMPC with the following formulation: To approximate the nonlinear dynamical function, we use its Jacobian at each time step: Note that the package contains the code generation ...
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