Multi-context systems in dynamic environments

Multi-context systems in dynamic environments

Multi-Context Systems (MCSs) are able to formally model, in Computational Logic, distributed systems composed of heterogeneous sources, or “contexts”, interacting via special rules called “bridge rules”. In this paper, we consider how to enhance flexibility and generality in bridge-rules definition...

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Veröffentlicht in:Annals of mathematics and artificial intelligence 2019-07, Vol.86 (1-3), p.87-120
Hauptverfasser: Cabalar, Pedro, Costantini, Stefania, De Gasperis, Giovanni, Formisano, Andrea
Format: Artikel
Sprache:eng
Schlagworte:
Artificial Intelligence
Complex Systems
Computer networks
Computer Science
Context
Knowledge
Logic programming
Mathematics
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Zusammenfassung:Multi-Context Systems (MCSs) are able to formally model, in Computational Logic, distributed systems composed of heterogeneous sources, or “contexts”, interacting via special rules called “bridge rules”. In this paper, we consider how to enhance flexibility and generality in bridge-rules definition and use. In particular, we introduce and discuss some formal extensions of MCSs aimed to their practical application in dynamic environments, and we provide guidelines for implementations.
ISSN:1012-2443
1573-7470
DOI:10.1007/s10472-019-09622-0