Non-local Optimization: Imposing Structure on Optimization Problems by Relaxation
@article{Mller2020NonlocalOI, title={Non-local Optimization: Imposing Structure on Optimization Problems by Relaxation}, author={Nils M{\"u}ller and T. Glasmachers}, journal={ArXiv}, year={2020}, volume={abs/2011.06064} }
In stochastic optimization, particularly in evolutionary computation and reinforcement learning, the optimization of a function $f: \Omega \to \mathbb{R}$ is often addressed through optimizing a so-called relaxation $\theta \in \Theta \mapsto \mathbb{E}_\theta(f)$ of $f$, where $\Theta$ resembles the parameters of a family of probability measures on $\Omega$. We investigate the structure of such relaxations by means of measure theory and Fourier analysis, enabling us to shed light on the… CONTINUE READING
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