@mastersthesis{,
  author={Martin Spott},
  title=\{Unscharfes Schließen mit komplexen Wissensbasen},
  year=\{1994},
  month=\{Jul},
  abstract=\{  Possibility distributions form a widely accepted method for   representing a certain type of uncertain knowledge. As yet, most   mechanisms for processing possibility distributions have been   founded on intuitive argumentation only. As a solution a   comprehensive, mathematically sound theory of possibility   distributions is proposed that is based on three simple axioms and   the Principle of Minimal Specificity. Possibilistic knowledge-bases   are represented by sets of possibility distributions. Inferring   information from a knowledge-base is interpreted as combining its   possibility distributions into the most specific one we are allowed   to infer. On these assumptions it is shown in particular that the   max-min-composition is an unambiguous mechanism for the aggregation   of possibility distributions that are defined on different and   freely chosen subspaces of a given cartesian product of   universes.      A special type of possibility distribution (Possibilistic   Relation of Dependence or PROD) is postulated as a   description of dependencies between variables. They play an   important role in a theory of possibilistic fuzzy systems that   is presented as a general framework for fuzzy modeling of real-world   problems.  The last chapter is dedicated to rule-based reasoning in the possibilistic setting, especially the use of the Gödel-relation for inference. },
}