MMP.8.SD:4.5 - Match the continuation to the uncertainty and objective

When the available information is a set of possible circumstances, evaluate a policy over the permitted complete trajectories. Compare its worst consequence, an interval or another requested result without inventing a probability distribution.

A stage-by-stage worst-case calculation is justified only if the retained description preserves which continuations remain possible. In particular, one unknown parameter fixed throughout a run cannot silently take a different worst value at each stage. Carry that parameter’s compatible set and any information learned about it, or keep the coupled trajectories. :5.4 shows a choice reversed by losing this dependence.

Likewise, a terminal threshold depends on the accumulated amount. Retain that amount if it is observed; otherwise retain the uncertainty about it together with the other relevant state. In :5.3, current expected gain is enough to compare one objective but insufficient for another.

For a compressed or learned state, separate three possible claims: performance of a specified restricted policy; an optimum within that policy class; and an optimum among all policies allowed by the available history. Neither a convenient memory representation nor a converged learning algorithm makes those claims interchangeable. Evaluate the returned policy under the original information and consequence account, with the uncertainty or approximation relevant to its intended use.