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An Agent-Environment Interaction Model

  • Scott A. DeLoach
  • Jorge L. Valenzuela
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4405)

Abstract

This paper develops a model for precisely defining how an agent interacts with objects in its environment through the use of its capabilities. Capabilities are recursively defined in terms of lower-level capabilities and actions, which represent atomic interactions with the environment. Actions are used to represent both sensors and effectors. The paper shows how the model can be used to represent both software and physical agents and their capabilities. The paper also shows how the model can be integrated into the Organization-based Multiagent Systems Engineering methodology.

Keywords

Global Position System Domain Model Multiagent System Environment Model Object Constraint Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    DeLoach, S.A.: Engineering Organization-based Multiagent Systems. In: Garcia, A., et al. (eds.) SELMAS 2005. LNCS, vol. 3914, pp. 109–125. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    DeLoach, S.A.: AgentTool III Home Page. Multiagent & Cooperative Robotics Laboratory (2006), http://macr.cis.ksu.edu/projects/agentTool/agentool3.htm
  3. 3.
    DeLoach, S.A., Wood, M.F., Sparkman, C.H.: Multiagent Systems Engineering. The International Journal of Software Engineering and Knowledge Engineering 11(3), 231–258 (2001)CrossRefGoogle Scholar
  4. 4.
    Ferber, J.: Multi-Agent Systems - An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Harlow (1999)Google Scholar
  5. 5.
    MESSAGE: Methodology for Engineering Systems of Software Agents. Deliverable 1. Initial Methodology. EURESCOM Project P907-GI (2000)Google Scholar
  6. 6.
    Odell, J., et al.: Modeling Agents and their Environments. In: Giunchiglia, F., Odell, J.J., Weiss, G. (eds.) AOSE 2002. LNCS, vol. 2585, pp. 16–31. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  7. 7.
    Padgham, L., Winikoff, M.: Prometheus: A Methodology for Developing Intelligent Agents. In: Giunchiglia, F., Odell, J.J., Weiss, G. (eds.) AOSE 2002. LNCS, vol. 2585, pp. 174–185. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    Pressman, R.: Software Engineering: A Practitioner’s Approach, 6th edn. McGraw-Hill, New York (2004)Google Scholar
  9. 9.
    Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 2nd edn. Prentice-Hall, Englewood Cliffs (2002)Google Scholar
  10. 10.
    Weyns, D., et al.: Environments for Multiagent Systems State-of-the-Art and Research Challenges. In: Dobbertin, H., Rijmen, V., Sowa, A. (eds.) AES 2005. LNCS, vol. 3373, pp. 1–47. Springer, Heidelberg (2005)Google Scholar
  11. 11.
    Wooldridge, M., Jennings, N., Kinny, D.: The Gaia methodology for agent-oriented analysis and design. Journal of Autonomous Agents and Multi-Agent Systems 3(3), 285–312 (2000)CrossRefGoogle Scholar
  12. 12.
    Zambonelli, F., Jennings, N.R., Wooldridge, M.J.: Developing Multiagent Systems: The Gaia methodology. ACM Transaction on Software Engineering Methodology 12(3), 317–370 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Scott A. DeLoach
    • 1
  • Jorge L. Valenzuela
    • 1
  1. 1.Department of Computing and Information Sciences, Kansas State University 234 Nichols Hall, Manhattan, KS 66506 

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