Reconciling Early and Late Time Tensions with Reinforcement Learning

Understand

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.