On Minimal Change in Evolving Multi-Context Systems (Preliminary Report)
  Managed Multi-Context Systems (mMCSs) provide a general framework for
integrating knowledge represented in heterogeneous KR formalisms. However,
mMCSs are essentially static as they were not designed to run in a dynamic
scenario. Some recent approaches, among them evolving Multi-Context Systems
(eMCSs), extend mMCSs by allowing not only the ability to integrate knowledge
represented in heterogeneous KR formalisms, but at the same time to both react
to, and reason in the presence of commonly temporary dynamic observations, and
evolve by incorporating new knowledge. The notion of minimal change is a
central notion in dynamic scenarios, specially in those that admit several
possible alternative evolutions. Since eMCSs combine heterogeneous KR
formalisms, each of which may require different notions of minimal change, the
study of minimal change in eMCSs is an interesting and highly non-trivial
problem. In this paper, we study the notion of minimal change in eMCSs, and
discuss some alternative minimal change criteria.
