Sequential diagnostic reasoning with independent causes

AbstractIn real world contexts of reasoning about evidence, that evidence frequently arrives sequentially. Moreover, we often cannot anticipate in advance what kinds of evidence we will eventually encounter. This raises the question of what we do to our existing models when we encounter new variables to consider. The standard normative framework for probabilistic reasoning yields the same ultimate outcome whether multiple pieces of evidence are acquired in sequence or all at once, and it is insensitive to the order in which that evidence is acquired. This equivalence, however, holds only if all potential evidence is incorporated in a single model from the outset. Hence little is known about what happens when evidence sets are expanded incrementally. Here, we examine this contrast formally and report the results of the first study, to date, that examines how people navigate such expansions.


Return to previous page