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Incorporating weather forecasts in the control of land surface water levels requires predicting the outcome of a control action. In Model-Predictive Control (MPC) such predictions are generated by a model of the water system. The actuators in this specific application typically cause discontinuities in this model. Avoiding complex solving techniques for such hybrid systems, this paper introduces an...
We present a novel batch-mode Reinforcement Learning approach for the design of optimal controllers in the presence of multiple objectives. The algorithm is an extension of Fitted Q-iteration (FQI) that enables to design the controller for all the linear combinations of preferences (weights) assigned to the objectives in a single run. The key idea of multi-objective FQI (MOFQI) is to enlarge the continuous...
Long range dependence is closely linked with self-similar stochastic processes and random fractals, which have been considered extensively for signal processing applications and computer network traffic modeling. The Hurst parameter captures the amount of long-range dependence in a time series. Typically, the analysis of self-similar series is performed using: the variance-time plot, the R/S plot,...
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