Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...
Abstract: This study explores the development of nonlinear activation functions in reinforcement learning through evolutionary computation. Traditional activation functions like Rectified Linear-Unit ...
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