Virtual Knowledge Communities for Semantic Agents

Julien Subercaze (1) , Pierre Maret (1)

1 LHC - Laboratoire Hubert Curien

Virtual Knowledge Communities are a well suited paradigm for decentralized knowldege exchanges and they have been applied in several domains. In this paper we investigate the implementation of virtual knowledge communities with se- mantic agents. Using the SAM (Semantic Agent Modeling) approach, we show that agents can exchange community re- lated concepts (in OWL) and behavior (in SWRL). Agents can then learn and adapt new community-related behavior, which is usefull when changing the role or entering into a new environment. For this purpose, we formalize Virtual Knowledge Communities in a set-theoretic way and we im- plement this formalization in an OWL ontology. Some ex- amples of community representation using our formalization are presented in this paper.

Domaines: Intelligence artificielle [cs.AI]

Julien Subercaze, Pierre Maret. Virtual Knowledge Communities for Semantic Agents. Web Intelligence, Mining and Semantics Conference, May 2011, Sogndal, Norway. pp. ⟨hal-00568897⟩