Conversely, Billhardt's model does not support the multi-context feature but is capable of transferring trust across contexts.
Managed multi-context systems (mMCSs) allow for the integration of heterogeneous knowledge sources in a modular and very general way.
This work has been developed for Morphosys, a coarse-grain multi-context reconfigurable architecture, and it can be successfully applied to systems with similar features.
More concretely, we consider the powerful framework of Multi-Context Systems, in which decentralized and heterogeneous system parts interact via (possibly nonmonotonic) bridge rules for information exchange.
In this paper, we introduce reactive multi-context systems (rMCSs), a framework for reactive reasoning in the presence of heterogeneous knowledge sources and data streams.
In this paper, we propose a multi-context graded BDI architecture (called n-BDI) that models norm-autonomous agents able to deal with uncertainty in dynamic environments.
Real-time crowd dynamics modeling and real-time activity modeling have been achieved by implementing the algorithms developed for Context Acquisition and multi-context fusion.
In this research note, we introduce a graded BDI agent development framework, g-BDI for short, that allows to build agents as multi-context systems that reason about three fundamental and graded mental attitudes (i.e. beliefs, desires and intentions).
Multi-context: As a single service provider may offer different services that require different competencies, a computational model should be able to reflect the context in which a service provider has established trust.
At the time of this study, there was not any multi-context database publicly available that could be used for the evaluation without additional processing, and we recorded and annotated our own audio database.
Dragoni [17] followed this vision to formalize the consequences of an utterance or series of dialogue acts on the mental state of the hearer in a multi-context framework.
