- Belief change is concerned with the manner in which a rational agent incorporates new information, along with some pre-existing beliefs. My work in this area has broadly fallen under the AGM tradition, in which the beliefs of an agent are captured in a formal setting. I am primarily interested in iterated belief change, belief change due to action, and practical applications.
- I am interested in using formal models developed in the AI community to analyze problems in Information Security. This work includes formal verification of cryptographic protocols, and it also includes the treatment of security issues that arise due to human judgement. I am particularly interested in the notion of knowledge-based trust, which refers to the way that an agent determines how to incorporate new information based on the accuracy of previous reports.
Knowledge Representation and Reasoning
- Knowledge representation and reasoning is a broad term for the branch of Artificial Intelligence that is concerned with modelling the way an intelligent agent represents information about the world, and draws conclusions from this information. Under this general heading, I have worked on preferences, answer set programming, and formal ontologies. On the practical side, I have also been working on using formal KR tools for reasoning about power usage on the Smart Grid.
- Beyond applications in AI, I also have research interests in more theoretical issues in Computational Logic. I am particularly interested in the Spectrum Problem, which is a long-standing open problem in Finite Model Theory.