BElief change FOR better MUlti-Source Information Analysis

The aim of this project is to perform an analysis of pieces of information coming from different sources. The idea is to be able to produce at the same time an assessment of the reliability of the sources and a coherent view of the world that takes into account the received pieces of information. This problem of trying to find the most plausible beliefs from different sources providing conflicting pieces of information is quite a frequent pattern. This is typically the case in applications in which one works with several sensors (that are typically not totally reliable), when one receives information from different agents (while some agents can be non-reliable, or, worse than that, with some agents being enemies trying to mislead you), or when one query several databases in order to answer to a query of a user. Our aim is to study the basic abstract problem, using tools mainly coming from the knowledge representation and reasoning (KR) area, in particular methods coming from belief revision and belief merging, that formalize rational belief change, as well as inconsistency measures, which allows us to measure the extent to which certain pieces of information are in conflict with each other.