The idea is that universal prior is really about observation-predicting algorithms that agents run, and not about prediction of what will happen in the world. So, for any agent that runs a given anticipation-defining algorithm and rewards/punishes the universal prior-based agent according to it, we have an anticipation-computing program that will obtain higher and higher probability in the universal prior-based agent.

This by the way again highlights the distinction between what will actually happen, and what a person anticipates - predictions are about capturing the concept of anticipation, an aspect of how people think, and are not about what in fact can happen.