Applications in control and/or monitoring usually demand an explicit representation and management of time. Fuzzy Temporal Rules (FTRs) introduce an explicit fuzzy representation of time, allowing relative occurrences of events, quantification, and other types of operators. In this model fuzziness can appear not only in the temporal references, but also in the sets of values and operators involved. This paper presents the most relevant features and applications of knowledge representation and reasoning within the FTRs framework. New challenges, both regarding automated learning of knowledge bases involving these rules and potential new fields of application in a number of areas, are also described.
Keywords: Fuzzy Temporal Rules, Fuzzy Temporal Reasoning, Evolutionary Fuzzy Systems