Multilingual Agents: Ontologies, Languages and Abstractions

Agent Environments are becoming increasingly open, interconnected and heterogeneous. This suggests that future agents will need to be able to deal with multiple agent communication languages, multiple ways of expressing content and multiple ontology representations. One way to deal with this heterogeneity is by identifying an agent's internal knowledge representation with an abstract ontology representation (AOR). This AOR then can be used to capture abstract models of communication related knowledge (domain models, agent communication languages, content languages and models of how these interact) and make it possible for the agent to manipulate all elements of messages in a uniform way as instances of its ontological knowledge. The paper outlines the approach, highlights interesting issues and describes a prototype implementation.