Diverse Web Ontologies: What Intelligent Agents Must Teach to Each Other

Andrew B. Williams and Costas Tsatsoulis

This paper describes our ongoing research in multiagent learning among intelligent agents with diverse ontologies for World Wide Web distributed knowledge sharing and integration. Much research has been done on agent knowledge sharing through the use of common, pre-defined ontologies. However, several domains, including the World Wide Web, often precipitate intelligent agents selfishly inventing ontologies based on their utility for the task at hand. If such agents are able and willing to teach each other concepts based on their individualized ontologies, then the entire group of agents can accomplish their group and individual tasks more efficiently and with more creativity. We describe the hypotheses we are investigating and our proposed methodology for multiagent learning with diverse ontologies using the World Wide Web domain.


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