Similarity measures of events, relational event algebra, and extensions to fuzzy logic

Considers the fuzzy logic extension of the problem of reconstructing events and their algebras of operators when the events are only implicitly described through numerical relations or functions involving probabilities of contributory events. This reconstruction has been obtained via a new mathematical technique called `relational event algebra´ (REA), extending previous efforts on the reconstruction of conditional events via conditional event algebra. An important new application of this work is to the determination of the degree of similarity or the distance between implicitly described events, models and inference rules. In carrying out the fuzzy logic extension of REA, compatibility with the one-point-coverage random set representation of fuzzy logic is taken into account