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Temporal and Spatial Analysis to Personalise an Agent’s Dynamic Belief, Desire, and Intention Profiles

  • Catholijn M. Jonker
  • Vagan Terziyan
  • Jan Treur
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2782)

Abstract

The paper addresses the dynamic belief, desire and intention profiles that can be made of an agent following a particular route, for example through a city. It assumes that location of an agent has effects on his beliefs desires and intentions and that the history of agent’s mobility and observed states in different locations can be used to predict his future states if the location is being permanently observed. A formal spatial route language is introduced. Formal relationships between the intentional notions, and the spatial behaviour of an agent are defined. As an application an information agent architecture for reasoning about the intentions of the customers of a mobile location-based service is described.

Keywords

Geographic Information System Mobile Terminal World Fact Belief Intention Desire Mobile Customer 
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.
    Berry, J.S., Belovsky, G., Joern, A., Kemp, W.P., Onsager, J.: Object-Oriented Simulation Model of Rangeland Grasshopper Population Dynamics. In: Proceedings of Fourth Annual Conference on AI, Simulation, and Planning in High Autonomy Systems, Tucson, AZ, September 20–22, pp. 102–108 (1993)Google Scholar
  2. 2.
    Blamey, S.: Partial Logic. In: Gabbay, D., Guenthner, F. (eds.) Handbook of Philosophical Logic, vol. III, pp. 1–70. Reidel, Dordrecht (1986)Google Scholar
  3. 3.
    Brazier, F.M.T., Dunin-Keplicz, B.M., Treur, J., Verbrugge, L.C.: Modelling Internal Dynamic Behaviour of BDI agents. In: Meyer, J.-J.C., Schobbens, P.-Y. (eds.) ModelAge-WS 1997. LNCS (LNAI), vol. 1760, pp. 36–56. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  4. 4.
    Briggs, D., Westervelt, J., Levi, S., Harper, S.: A Desert Tortoise Spatially Explicit Population Model. In: Third International Conference. Integrating GIS and Environmental Modeling, Santa Fe, NM, January 21–25 (1996)Google Scholar
  5. 5.
    Cohen, P.R., Levesque, H.J.: Intention is Choice with Commitment. Artificial Intelligence 42, 213–261 (1990)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Gimblett, H.R., Itami, R.M., Durnota, D.: Some Practical Issues in Designing and Calibrating Artificial Human-Recreator Agents in GIS-based Simulated Worlds. In: Workshop on Comparing Reactive (ALife-ish) and Intentional Agents. Complexity International, vol. 3 (1996)Google Scholar
  7. 7.
    Green, D.G.: Spatial Simulation of fire in Plant Communities. In: Wise, P. (ed.) Proceedings of National Symposium on Computer Modeling and Remote Sensing in Bushfire Prevention, National Mapping, Canberra, pp. 36–41 (1987)Google Scholar
  8. 8.
    Itami, R.M., Gimblett, H.R.: Intelligent recreation agents in a virtual GIS world. In: Complexity International, vol. 8 (2001)Google Scholar
  9. 9.
    Jonker, C.M., Treur, J., de Vries, W.: Temporal Analysis of the Dynamics of Beliefs, Desires, and Intentions. Cognitive Science Quarterly 2, 471–494 (2002)Google Scholar
  10. 10.
    van Linder, B., van der Hoek, W., Meyer, J.-J.C.: How to motivate your agents: on making promises that you can keep. In: Tambe, M., Müller, J., Wooldridge, M.J. (eds.) IJCAI-WS 1995 and ATAL 1995. LNCS, vol. 1037, pp. 17–32. Springer, Heidelberg (1996)Google Scholar
  11. 11.
    Rao, A.S., Georgeff, M.P.: Modelling Rational Agents within a BDI-Architecture. In: Allen, J., Fikes, R., Sandewall, E. (eds.) Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning (KR 1991), pp. 473–484. Morgan Kaufmann, San Francisco (1991)Google Scholar
  12. 12.
    Saarenmaa, H., Perttunen, J., Vakeva, J., Nikula, A.: Object-oriented modeling of the tasks and agent in integrated forest health management. AI Applications in Natural Resource Management 8(1), 43–59 (1994)Google Scholar
  13. 13.
    Slothower, R.L., Schwarz, P.A., Johnson, K.M.: Some Guidelines for Implementing Spatially Explicit, Individual-Based Ecological Models within Location-Based Raster GIS. In: Third International Conference Integrating GIS and Environmental Modeling, Santa Fe, NM, January 21–25 (1996)Google Scholar
  14. 14.
    Virrantaus, K., Veijalainen, J., Markkula, J., Katasonov, A., Garmash, A., Tirri, H., Terziyan, V.: Developing GIS-Supported Location-Based Services. In: Proceedings of WGIS 2001 - First International Workshop on Web Geographical Information Systems, Kyoto, Japan, December 3-6, pp. 423–432 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Catholijn M. Jonker
    • 1
  • Vagan Terziyan
    • 2
  • Jan Treur
    • 1
  1. 1.Department of Artificial IntelligenceVrije Universiteit AmsterdamAmsterdamThe Netherlands
  2. 2.Department of Mathematical Information TechnologyUniversity of JyvaskylaJyvaskylaFinland

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