Agent to Agent Talk: “Nobody There?” Supporting Agents Linguistic Communication

  • Maria Teresa Pazienza
  • Michele Vindigni
Conference paper
Part of the Whitestein Series in Software Agent Technologies book series (WSSAT)


World-Wide Web technologies and the vision of Semantic Web have pushed for adaptive SW applications to scale up information technologies to the Web, where information is organized following different underlying knowledge and/or presentation models. Interoperability among heterogeneous intelligent agents has become an important research topic in the context of distributed information systems. Communication among heterogeneous agents involves several dimensions. “Ontological commitment” on a shared knowledge model cannot be assumed as a default.

To overcome this problem, we will describe in this article a communication model that bases on the use of natural language. We will argue on main topics involved in using natural language to achieve semantic agreement in agents communication. The model foresees a strong separation among terms and concepts, this difference being often undervalued in the literature, where terms play the ambiguous role of both concept labels and of communication lexicon. For agents communicating through the language, lexical information embodies instead the possibility to “express” the underlying conceptualizations thus agreeing to a shared representation. We will examine in details the different layers involved in agents communication and we will focus on a the different roles played by each element. A novel agent architecture able to tackle with possible linguistic ambiguities by focusing on the conversational level will be deeply described. Three different agent typologies will be presented: Resource agents, embodying the target knowledge, Service agents, providing basic skills to support complex activities and control agents, supplying the structural knowledge of the task, with coordination and control capabilities. NL communication is supported by two dedicated Service agents: a Mediator, that will handle conceptual mismatches arising during communication, and a Translator, dealing with lexical misalignments due to different languages/idioms.


Intelligent agents NLP semantic web ontology sharing 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    M. Q. W. Baldonado. An interactive, structure-mediated approach to exploring information in a heterogeneous, distributed environment. Ph.D. Dissertation, Stanford University, 1997.Google Scholar
  2. [2]
    Roberto Basili, Michele Vindigni, and Fabio Massimo Zanzotto. Integrating ontological and linguistic knowledge for conceptual information extraction. In Proc. of the IEEE/WIC International Conference on Web Intelligence (WI’03), Halifax (Canada), 2003.Google Scholar
  3. [3]
    R. J. Bayardo, Jr., W. Bohrer, R. Brice, A. Cichocki, J. Fowler, A. Helal, V. Kashyap, T. Ksiezyk, G. Martin, M. Nodine, M. Rashid, M. Rusinkiewicz, R. Shea, C. Unnikrishnan, A. Unruh, and D. Woelk. InfoSleuth: Agent-based semantic integration of information in open and dynamic environments. In Proceedings of the ACM SIGMOD International Conference on Management of Data, volume 26,2, pages 195–206, New York, 13–15 1997. ACM Press.Google Scholar
  4. [4]
    S. Bergamaschi, S. Castano, S. di Vimercati, S. Montanari, and M. Vincini. An intelligent approach to information integration. In Proc.s of the International Conference on Formal Ontology in Information Systems (FOIS’98), Trento, Italy, 1998.Google Scholar
  5. [5]
    A. Campbell, H. Chalupsky, and S. Shapiro. Ontological mediation: An analysis. unpublished manuscript.Google Scholar
  6. [6]
    C. K. Chang and H. Garcia-Molina. Conjunctive constraint mapping for data translation. In Proceedings of the Third ACM International Conference on Digital Libraries, Pittsburgh, Pa., 1998. ACM Press, New York.Google Scholar
  7. [7]
    S. Chawathe, H. Garcia-Molina, J. Hammer, K. Ireland, Y. Papakonstantinou, J. D. Ullman, and J. Widom. The TSIMMIS project: Integration of heterogeneous information sources. In 16th Meeting of the Information Processing Society of Japan, pages 7–18, Tokyo, Japan, 1994.Google Scholar
  8. [8]
    W. W. Cohen and H. Hirsh. Learning the CLASSIC description logic: Theoretical and experimental results. In Principles of Knowledge Representation and Reasoning: Proceedings of the Fourth International Conference (KR94). Morgan Kaufmann, 1994.Google Scholar
  9. [9]
    A. Farquhar, R. Fikes, and J. Rice. The ontolingua server: A tool for collaborative ontology construction. In Technical report, Stanford KSL 96-26, 1996.Google Scholar
  10. [10]
    D. Fensel, S. Decker, M. Erdmann, and R. Studer. Ontobroker in a nutshell. In European Conference on Digital Libraries, pages 663–664, 1998.Google Scholar
  11. [11]
    T. Finin, R. Fritzson, D. McKay, and R. McEntire. KQML as an Agent Communication Language. In N. Adam, B. Bhargava, and Y. Yesha, editors, Proceedings of the 3rd International Conference on Information and Knowledge Management (CIKM’94), pages 456–463, Gaithersburg, MD, USA, 1994. ACM Press.Google Scholar
  12. [12]
    Foundation for Intelligent Physical Agents. FIPA 97 specification part 2: Agent communication language, October 1997. Version 2.0.Google Scholar
  13. [13]
    M. R. Genesereth and R. E. Fikes. Knowledge Interchange Format, Version 3.0 Reference Manual. Technical Report Logic-92-1, Computer Science Department, Stanford University, Stanford, CA, USA, June 1992.Google Scholar
  14. [14]
    P. Gennari and J. Musen. Mappings for reuse in knowledge-based systems. In 11 th Workshop on Knowledge Acquisition, Modelling and Management KAW 98, Banff, Canada, 1998.Google Scholar
  15. [15]
    N. Guarino and R. Poli. Formal ontology in conceptual analysis and knowledge representation. In Special issue of the International Journal of Human and Computer Studies, vol. 43 n. 5/6, Academic Press., 1995.Google Scholar
  16. [16]
    R. V. Guha and Douglas B. Lenat. Enabling agents to work together. Commun. ACM, 37(7):126–142, 1994.CrossRefGoogle Scholar
  17. [17]
    J. Heflin, J. Hendler, and S. Luke. SHOE: A knowledge representation language for internet applications. Technical Report CS-TR-4078, 1999.Google Scholar
  18. [18]
    R. Hull. Managing semantic heterogeneity in databases: a theoretical prospective. In Proc. ACM Symposium on Principles of Databases (Invited Tutorial), pages 51–61, 1997.Google Scholar
  19. [19]
    V. Kashyap and A. P. Sheth. Semantic and schematic similarities between database objects: A context-based approach. VLDB Journal: Very Large Data Bases, 5(4):276–304, 1996.CrossRefGoogle Scholar
  20. [20]
    C. A. Knoblock and J. L. Ambite. Agents for information gathering. In Jeffrey M. Bradshaw, editor, Software Agents, pages 347–374. AAAI Press / The MIT Press, 1997.Google Scholar
  21. [21]
    W.S. Li. Knowledge gathering and matching in heterogeneous databases. In AAAI Spring Symposium on Information Gathering, 1995.Google Scholar
  22. [22]
    M. T. Pazienza, A. Stellato, and M. Vindigni. Purchasing the web: an agent based eretail system with multilingual knowledge. In Proc. of the IEEE/WIC International Conference on Web Intelligence (WI’03), Halifax, Canada, 2003.Google Scholar
  23. [23]
    M. T. Pazienza and M. Vindigni. Language-based agent communication. In proceedings of EKAW02, 13th International Conference on Knowledge Engineering and Knowledge Management, OMAS Workshop on Ontologies for Multi-Agent Systems, Siguenza, Spain, 2002.Google Scholar
  24. [24]
    M. T. Pazienza and M. Vindigni. Agent Based Ontological Mediation in IE Systems. In Lecture Notes in Artificial Intelligence LNAI 2700, Springer Verlag, Berlin Heidelberg, 2003.Google Scholar
  25. [25]
    M.T. Pazienza, A. Stellato, M. Vindigni, A. Valarokos, and V. Karkaletsis. Ontology integration in a multilingual e-retail system. In HCI International 2003, 10th International Conference on Human-Computer Interaction, Crete (Greece), 2003.Google Scholar
  26. [26]
    J. R. Searle. Speech Acts: An Essay in the Philosophy of Language. Cambridge University Press, Cambridge, England, 1969.Google Scholar
  27. [27]
    John F. Sowa. Knowledge representation: logical, philosophical and computational foundations. Brooks/Cole Publishing Co., 2000.Google Scholar
  28. [28]
    John F. Sowa. Ontology, metadata, and semiotics. In Proceedings of the Linguistic on Conceptual Structures, pages 55–81. Springer-Verlag, 2000.Google Scholar
  29. [29]
    Gerhard Weiss, editor. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. The MIT Press, Cambridge, MA, USA, 1999.Google Scholar
  30. [30]
    G. Wiederhold and M. R. Genesereth. The conceptual basis for mediation services. IEEE Expert, 12(5):38–47, 1997.CrossRefGoogle Scholar
  31. [31]
    W. Wilks. Senses and texts. In N. Ide (ed.) special issue of Computers and the Humanities, 31(2)., 1997.Google Scholar
  32. [32]
    M. J. Wooldridge and N. R. Jennings. Intelligent Agents — Theories, Architectures, and Languages, volume 890 of Lecture Notes in Artificial Intelligence. Springer-Verlag: Heidelberg, Germany, 1995.Google Scholar

Copyright information

© Birkhäuser Verlag 2005

Authors and Affiliations

  • Maria Teresa Pazienza
    • 1
  • Michele Vindigni
    • 2
  1. 1.Dept. of Computer Science, Systems and ProductionUniversity of Rome “Tor Vergata”RomeItaly
  2. 2.University of BresciaBresciaItaly

Personalised recommendations