How does KEEL address probabilistic information and fuzzy problems?
This is a two part question. First, with probabilistic information, one assumes that statistics and probabilities are available to be used to interpret the information. Formal statistics are commonly used as inputs to a KEEL Engine when they are available. The following example shows a system where two options are considered. In this case the probability input is through input 0 and the two options are input through inputs 1 and 2. If the “probability” is set to 50 (meaning equal or 50/50), then if options 1 and 2 are equal there is an equal probability and either option is a viable choice. With KEEL, there is never confusion about which one to choose. It finds the first value with the highest rated answer. In this case option 1 is indicated with the icon. Manipulating the probability input (0) and/or the Option 1 or 2 inputs (which would correspond to a confidence value or quality of information value), will allow the system to re-evaluate the information. The second part of the quest
