A planner keeps two excellent action sequences. It fits a new sampling distribution to those elites. Half the probability then goes to sequences that were explicitly rejected.

No indexing error is required. The result follows from the distribution family being fitted.

We can see it by solving one existing TensorDrill problem, Update a Categorical CEM Planning Distribution . The task is a single unsmoothed update: select low-cost sequences, then calculate each action's elite frequency separately at each time step.

The counterexample below uses exact supplied costs. It does not require an inaccurate world model. That makes it a useful way to isolate a planning assumption before adding prediction error.

Two good plans, four possible combinations

Consider two action IDs, 0 and 1 , and a horizon of two steps.…