MMP.8.SD:6 - Bias-Annotation

Finite stochastic examples make expectations and recursion easy to inspect, but may encourage a probability model or scalar gain where neither is supplied. Keep non-probabilistic possibilities and multiple criteria when that is what the work supports.

A model with one decision maker can also conceal separate information held by different people or systems. Represent communication and its timing when the proposed continuation depends on shared knowledge. Learned memory is attractive in large problems; its convenience does not establish sufficiency for a changed action set or criterion.