Hybrid domains are those featuring a mix of discrete and continuous variables. Recent research has resulted in sophisticated general purpose languages for modeling hybrid domains such as PDDL+ and H as well as efficient planning algorithms based on translation to logical formalisms. However, other reasoning tasks, such as execution monitoring and diagnosis, have not received as much attention. In this thesis, we address this shortcoming and propose execution monitoring and diagnostic reasoning algorithms based on action language H together with an agent architecture that combines planning, diagnostics, and execution monitoring for hybrid domains. The algorithms are based on an expanded translation of action language H to Constraint Answer Set Programming (CASP), which we developed for this project. We demonstrate our approach on two simple, but non-trivial scenarios including one that we tested on an actual robot.M.S.S.E., Software Engineering -- Drexel University, 201
