Decision and Reasoning in Incompleteness or Uncertainty Conditions

Abstract

When we try to solve new or known problems to which we want to give new solutions, we create new knowledge and realize new discoveries. To date, the scientific methods have used the probability in order to analyze problems, make inference and build forecasts. However, everyone agreed that most problems do not follow standard probabilistic rules. In this study we will build an uncertainty logic by using the concept of probability, with those of plausibility, credibility and possibility. We will provide several models which treats uncertainty information and allow to perform more reliable forecasts. After that, we will prove the models reliability through a final simulation on the Biometrics and Sport fields using one of the models; these simulation are fully replicabile for each field and for each of the provided models.