When executing a Decision Strategy that includes an Adaptive Model component mapped to three propositions, how many adaptive models are created? (Choose One)

In Pega Decisioning, when working with an Adaptive Model component that is mapped to multiple propositions, a distinct Adaptive Model is created for each proposition in the strategy. This means that if there are three propositions involved, each proposition will have its own Adaptive Model tailored to learn from the specific interactions associated with that proposition.

Furthermore, an additional Adaptive Model is often created to capture the baseline behavior or general trends that are not specific to any proposition. Therefore, for three propositions, you have three individual Adaptive Models plus one additional model, resulting in a total of four Adaptive Models. This is why the number of adaptive models created in this scenario is four, making it clear that the correct choice is the total accounting for each proposition plus the baseline, leading us to the conclusion that the answer indicates a misunderstanding regarding how adaptive learning functions in this context.

In summary, for any decision strategy that incorporates Adaptive Models connected to multiple propositions, the total count of adaptive models reflects not only the mappings to those propositions but also the necessity for an overarching model that signifies broader behavioral insights, thus leading to the correct conclusion.