Ontologies for Agents: Theory and Experiences

  • Valentina Tamma
  • Stephen Cranefield
  • Timothy W. Finin
  • Steven Willmott
Conference proceedings

Part of the Whitestein Series in Software Agent Technologies book series (WSSAT)

Table of contents

  1. Front Matter
    Pages i-x
  2. Stephen Cranefield, Martin Purvis, Mariusz Nowostawski, Peter Hwang
    Pages 1-17
  3. Marian H. Nodine, Jerry Fowler
    Pages 19-42
  4. Dejing Dou, Drew McDermott, Peishen Qi
    Pages 73-94
  5. Kendall Lister, Maia Hristozova, Leon Sterling
    Pages 121-144
  6. Heiner Stuckenschmidt, Frank van Harmelen, Fausto Giunchiglia
    Pages 145-167
  7. Chris van Aart, Bob Wielinga, Guus Schreiber
    Pages 169-200
  8. Muthukkaruppan Annamalai, Leon Sterling
    Pages 201-231
  9. Harry Chen, Tim Finin, Anupam Joshi
    Pages 233-258
  10. Stephen Cranefield, Jin Pan, Martin Purvis
    Pages 259-276
  11. Ian Dickinson, Michael Wooldridge
    Pages 277-298
  12. Akio Sashima, Noriaki Izumi, Koichi Kurumatani
    Pages 299-321
  13. Roland Zimmermann, S. Käs, Robert Butscher, Freimut Bodendorf
    Pages 323-345

About these proceedings


There is a growing interest in the use of ontologies for multi-agent system app- cations. On the one hand, the agent paradigm is successfully employed in those applications where autonomous, loosely-coupled, heterogeneous, and distributed systems need to interoperate in order to achieve a common goal. On the other hand, ontologies have established themselves as a powerful tool to enable kno- edge sharing, and a growing number of applications have bene?ted from the use of ontologies as a means to achieve semantic interoperability among heterogeneous, distributed systems. In principle ontologies and agents are a match made in heaven, that has failed to happen. What makes a simple piece of software an agent is its ability to communicate in a ”social” environment, to make autonomous decisions, and to be proactive on behalf of its user. Communication ultimately depends on und- standing the goals, preferences, and constraints posed by the user. Autonomy is theabilitytoperformataskwithlittleornouserintervention,whileproactiveness involves acting autonomously with no need for user prompting. Communication, but also autonomy and proactiveness, depend on knowledge. The ability to c- municate depends on understanding the syntax (terms and structure) and the semantics of a language. Ontologies provide the terms used to describe a domain and the semantics associated with them. In addition, ontologies are often comp- mented by some logical rules that constrain the meaning assigned to the terms. These constraints are represented by inference rules that can be used by agents to perform the reasoning on which autonomy and proactiveness are based.


Processing Unified Modeling Language (UML) automated reasoning modeling multi-agent system ontology ubiquitous computing

Editors and affiliations

  • Valentina Tamma
    • 1
  • Stephen Cranefield
    • 2
  • Timothy W. Finin
    • 3
  • Steven Willmott
    • 4
  1. 1.Agent Applications, Research and Technology Group, Department of Computer ScienceUniversity of LiverpoolLiverpoolGreat Britain
  2. 2.Department of Information ScienceUniversity of OtagoDunedinNew Zealand
  3. 3.329 Information Technology and EngineeringUniversity of MarylandBaltimoreUSA
  4. 4.Dept. Llenguatges i Sistemes InformaticsUniversitat Politècnica de Catalunya (UPC)BarcelonaSpain

Bibliographic information