Supervisor

Suitable for

Abstract

Formal methods for analysing models such as Markov chains and Markov decision processes can be extended to explicitly reason about model uncertainty, for example by building and analysing interval Markov decision processes. This project will investigate alternative approaches to tackling this problem, which could include alternative models of transition probability uncertainty, factoring in dependencies between different sources of uncertainty, or using bayesian inference to learn model parameters.