(27th-May-2020)
The use of pseudocounts also gives us a way to combine expert opinion and data. Often a single agent does not have good data but may have access to multiple experts who have varying levels of expertise and who give different probabilities.
There are a number of problems with obtaining probabilities from experts:
experts' reluctance to give an exact probability value that cannot be refined,
representing the uncertainty of a probability estimate,
combining the numbers from multiple experts, and
combining expert opinion with actual data.
Rather than expecting experts to give probabilities, the experts can provide counts. Instead of giving a real number such as 0.667 for the probability of A, an expert can give a pair of numbers as ⟨n,m⟩ that can be interpreted as though the expert had observed n A's out of m trials. Essentially, the experts provide not only a probability but also an estimate of the size of the data set on which their opinion is based.
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