Evolving Bridge Rules in Evolving Multi-Context Systems

In open environments, agents need to reason with knowledge from various sources, represented in different languages. Managed Multi-Context Systems (mMCSs) allow for the integration of knowledge from different heterogeneous sources in an effective and modular way, where so-called bridge rules express how information flows between the contexts. The problem is that 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. These approaches, however, only consider the dynamics of the knowledge bases, whereas the dynamics of the bridge rules, i.e., the dynamics of how the information flows, is neglected. In this paper, we fill this gap by building upon the framework of eMCSs by further extending it with the ability to update the bridge rules of each context taking into account an incoming stream of observed bridge rules. We show that several desirable properties are satisfied in our framework, and that the important problem of consistency management can be dealt with in our framework.