Aggregation with Probability
With the introduction of probabilities, many existing aggregators are augmented with new semantics, which we typically call multi-world semantics.
What's more, there are new aggregators, such as softmax, rank, and weighted_avg, that make use of the probabilities.
We introduce these aggregators one-by-one in this section.
Multi-world Semantics with Aggregators
Let us take the count aggregator as an example.
Consider we have 2 objects, each could be big or small with their respective probabilities:
type OBJ = OBJ_A | OBJ_B
rel size = {0.8::(OBJ_A, "big"); 0.2::(OBJ_A, "small")} // obj A is very likely big
rel size = {0.1::(OBJ_B, "big"); 0.9::(OBJ_B, "small")} // obj B is very likely small
Now let's say we want to count how many big objects are there, by using the following
Note that even when using probabilites, one can opt to not use the multi-world semantics by adding ! sign to the end of the aggregator.