How to update/merge logical databases with the aim of maximising truth and relevance

Under the umbrella of knowledge representation and reasoning, logical database updating is the process of updating such a database when it receives new data, especially if the new data conflicts with some that already exists in the database. The related field of database merging or information fusion is about combining more than one, possibly mutually inconsistent, set of databases. The logical formalization of these procedures is researched in artificial intelligence and philosophy (where they are known as belief revision and belief merging) for the design of rational agents.

This project will involve some research into the basic issue that current formal methods used for the updating/merging of logical databases are not adequately equipped to deal with the aim of getting results that maximise the properties of truth and relevance. By combining methods of database updating/merging with formal measures that quantify truth, truthlikeness and relevance, new approaches that consider these valuable properties can be explored.

Expected background: Logic, knowledge representation.

Preferred/other background: Database/belief revision/merging, probability, Prolog