  We study the possibility of accommodating both early and late-time tensions
using a novel reinforcement learning technique. By applying this technique, we
aim to optimize the evolution of the Hubble parameter from recombination to the
present epoch, addressing both tensions simultaneously. To maximize the
goodness of fit, our learning technique achieves a fit that surpasses even the
$\Lambda$CDM model. Our results demonstrate a tendency to weaken both early and
late time tensions in a completely model-independent manner.
