Agents Interoperability based on NLP, able of meta-reasoning in the Semantic Web
What is it about?
In this paper we present a framework that instantiates cognitive agents operating in IoT context, endowed with meta-reasoning in the Semantic Web. The framework, called SW-Caspar, is also provided with a module that performs semi-automatic ontology learning from sentences expressed in natural language; such a learning process generates a conceptual space reflecting the domain of discourse with an instance of a novel foundational ontology called Linguistic Oriented Davidsonian Ontology (LODO), whose main feature is to increase the deepness of reasoning without compromising linguistic-related features. LODO is inspired by the First-Order Logic Davidsonian notation and serialized in OWL 2.
Why is it important?
Our aim is to facilitate or allow (where not possible) the interoperability among IoT agents, by leveraging also human fashioned meta-reasoning in the Semantic Web, in order to istantiate cognitive agents.