Abstract
An expert system “Jurassic” from the field of paleontology for the determination of a dinosaur species is presented. It helps the paleontologist to determine creatures from uncertain knowledge. The system is composed of 423 rules arranged in a directed acyclic graph of a depth of five. This knowledge is represented by a taxonomical arrangement of verbal categories represented by associative memories. Categorical representation is psychologically motivated and also offers an explanation of how to deal with uncertain knowledge. It is an alternative to other well known uncertainty calculi. During the categorization the model learns to favor these categories which often lead to a successful goal. This may help to speed up the search. Experiments with the availability heuristic in which parts of the knowledge base are primed or forgotten are performed.
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