01/01/19 12:10

MEMBERS

Principal Investigators: Manuel Ojeda-Aciego (PI1); Nicolás Madrid (PI2)
Investigators: Domingo López-Rodríguez; Emilio Muñoz-Velasco; Inmaculada Fortes; Agustín Valverde

SUMMARY

Due to the inherent incompleteness of our different information sources, handling imperfect information is a fundamental and unavoidable feature of everyday life. The adequate management of imperfect information is essential in applications, not only in Artificial Intelligence, but also in Social Sciences.
This proposal is determined by our long-term vision: the adequate languages for this framework should be based on the formal grounds of algebra and logic.
Analyzing the state-of-the-art on algebraic, logic, and fuzzy approaches to the management of imperfect information, our initial hypothesis is based on the following premises:
  • Many real-world problems are difficult to formalize by using classical methods, and a more general formal framework is needed in which approximate reasoning and/or imperfect information comes into play.
  • Further efforts are needed on foundational research about imperfect information so that unifying approaches can be found by abstracting particular details and extracting the basic mechanisms of execution.
  • This foundational research has to be necessarily done on a step-by-step basis. This is why we focus on specific topics in which our research team has proven proficiency, and we propose a scheme in which we will work in parallel in several lines.
Our long-term vision should lead to a thorough formal theory of imperfect information, and the expected breakthrough towards this aim is the development of foundations for certain selected areas of interest, namely, the study of the mathematical and logic-based approaches to imperfect information, fuzzy inference systems using F-transform and measures of inconsistency, and a case study on Digital Forensics.