Cross-community interoperation between knowledge-based multi-agent systems: A study on EMERALD and Rule Responder

  • Authors:

  • Kalliopi Kravari;Nick Bassiliades;Harold Boley

  • Affiliations:

  • Department of Informatics, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece;Department of Informatics, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece;Institute for Information Technology, NRC Canada, Fredericton, NB, Canada E3B 9W4

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

The ultimate vision of the Semantic Web (SW) is to provide users with the capability of delegating complex tasks to intelligent agents. The latter, acting in an interoperable and information-rich Web environment, will efficiently satisfy their users' requests in a variety of real-life applications. Much work has been done on SW information agents for Web-based query answering; a variety of multi-agent platforms and Web language standards has been proposed. However, the platform- and language-bridging interoperation across multi-agent systems has been neglected so far, although it will be vital for large-scale agent deployment and wide-spread adoption of agent technology by human users. This article defines the space of possible interoperation methods for heterogeneous multi-agent systems based on the communication type, namely symmetric or asymmetric, and the MASs status, namely open or closed systems. It presents how heterogeneous multi-agent systems can use one of these methods to interoperate and, eventually, automate collaboration across communities. The method is exemplified with two SW-enabled multi-agent systems, EMERALD and Rule Responder, which assist communities of users based on declarative SW and multi-agent standards such as RDF, OWL, RuleML, and FIPA. This interoperation employs a declarative, knowledge-based approach, which enables information agents to make smart and consistent decisions, relying on high-quality facts and rules. Multi-step interaction use cases between agents from both communities are presented, demonstrating the added value of interoperation.