Algorithms for Inconsistency Measurement

• Applicant: Professor Dr. Matthias Thimm
• Subject Area: Theoretical Computer Science ; Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 506604007

The objective of the proposed project is the development and evaluation of new algorithmic approaches to inconsistency measurement. The latter is a research field concerned with the development of measures that quantitatively assess the severity of inconsistency in logical knowledge bases. Inconsistency measures can be used to compare different formalisations of knowledge, to help debug flawed knowledge bases, and guide automatic repair methods. For example, inconsistency measures have been used to estimate reliability of agents in multi-agent systems, to analyse inconsistencies in news reports, to support collaborative software requirements specifications, to allow for inconsistency-tolerant reasoning in probabilistic logic, and to monitor and maintain quality in database settings. In AIM, we will develop a series of algorithms for a wide range of inconsistency measures. In particular, we will employ a diverse set of problem solving paradigms, such as satisfiability (SAT) solving, answer set programming (ASP), automated planning, and others, to approach the computation of inconsistency measures of various complexities and to find the best possible algorithms. We will analyse the practical performance of these algorithms with in-depth experimental evaluations and create a comprehensive repository of benchmarks for future algorithmic studies. Achieving the overall objective of AIM to create practical systems for inconsistency measurement will allow a more scalable application of inconsistency measures in the mentioned applications domains and beyond.

• DFG Programme: Research Grants