The Rescorla-Wagner model treats a stimulus as a single entity, and it represents the associative strength of a stimulus with one number, with no record of how that number was reached. As noted above, this makes it hard for the model to account for a number of experimental results. More flexibility is provided by assuming that a stimulus is internally represented by a collection of elements, each of which may change from one associative state to another. For example, the similarity of one stimulus to another may be represented by saying that the two stimuli share elements in common. These shared elements help to account for stimulus generalization and other phenomena that may depend upon generalization. Also, different elements within the same set may have different associations, and their activations and associations may change at different times and at different rates. This allows element-based models to handle some otherwise inexplicable results.