The question of "as if" rationality - that is, whether selfishly-minded, myopic agents may learn to

Current test-time adaptation (TT A) approaches aim to adapt a machine learning model to environments that change continuously.

In the classical decision-making literature, this is achieved by two interweaving processes, policyevaluation and policyimprovement (Sutton and Barto,2018).

Specifically, we integrate two essential sub-tasks, i.e., traffic data imputation and decision-making, by leveraging a Partial Rewards Conditioned Diffusion (PRCD) model to prevent missing rewards