  Subset models provide a new semantics for justifcation logic. The main idea
of subset models is that evidence terms are interpreted as sets of possible
worlds. A term then justifies a formula if that formula is true in each world
of the interpretation of the term. In this paper, we introduce a belief
expansion operator for subset models. We study the main properties of the
resulting logic as well as the differences to a previous (symbolic) approach to
belief expansion in justification logic.
