Virtual knowledge communities for semantic agents

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 semantic agents. Using the SAM (Semantic Agent Modeling) approach, we show that agents can exchange community related 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 implement this formalization in an OWL ontology. Some examples of community representation using our formalization are presented in this paper.

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