How Artificial Intelligent Agents Do Shopping in a Virtual Mall: A ‘Believable’ and ‘Usable’ Multiagent-Based Simulation of Customers’ Shopping Behavior in a Mall

  • Walid Ali
  • Bernard Moulin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4013)


Our literature review revealed that several applications successfully simulate certain kinds of human behaviors in spatial environments, but they have some limitations related to the ‘believability’ and the ‘usability’ of the simulations. This paper aims to present a set of requirements for multiagentbased simulations in terms of ‘believability’ and ‘usability’. It also presents how these requirements have been put into use to develop a multiagent-based simulation prototype of customers’ shopping behavior in a mall. Using software agents equipped with spatial and cognitive capabilities, this prototype can be considered sufficiently ‘believable’ and ‘usable’ for end-users, mainly mall managers in our case. We show how shopping behavior simulator can support the decision-making process with respect to the spatial configuration of the shopping mall.


MultiAgent System Shopping Mall Shopping Behavior Mall Manager Shopping Trip 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Anu, M.: Introduction to modeling and simulation. In: Proceedings of the 29th Conference on Winter Simulation, Atlanta, Georgia, December 07-10, 1997, pp. 7–13 (1997)Google Scholar
  2. 2.
    Bandinin, S., Manzoni, S., Simone, C.: Heterogeneous agents situated in heterogeneous spaces. Applied Artificial Intelligence 16(9-10), 831–852 (2002)CrossRefGoogle Scholar
  3. 3.
    Batty, M.: Agent-Based Pedestrian Modeling. CASA UCL Working papers series 61 (2003)Google Scholar
  4. 4.
    Bédard, Y., Rivest, S., Proulx, M.J.: Spatial On-Line Analytical Processing (SOLAP): Concepts, Architectures and Solutions from a Geomatics Engineering Perspective. In: Data Warehouses and OLAP: Concepts, Architectures and Solutions, Idea Group Publishing, USA (in press, 2005)Google Scholar
  5. 5.
    Dijsktra, J., Harry, J.-P., Bauke, U.: Virtual reality-based simulation of user behavior within the build environment to support the early stages of building design. In: Schreckenberg, M., Sharma, S.D. (eds.) Pedestrian and Evacuation Dynamics, pp. 173–181. Springer, Heidelberg (2001)Google Scholar
  6. 6.
    Frank, A.U., Bittner, S., Raubal, M.: Spatial and cognitive simulation with multi-agent systems, in D. In: Montello, D.R. (ed.) COSIT 2001. LNCS, vol. 2205, pp. 124–139. Springer, Heidelberg (2001)Google Scholar
  7. 7.
    ISO/IEC: 9241-14 Ergonomic requirements for office work with visual display terminals (VDT)s- Part 14 Menu dialogues, ISO/IEC 9241-14 (1998)Google Scholar
  8. 8.
    Koch, A.: Linking Multi-Agent Systems and GIS- Modeling and simulating spatial interactions-. Department of Geography RWTH Aachen. In: Angewandte Geographische Informationsverarbeitung XII, Beiträge zum AGIT-Symposium Salzburg 2000, Hrsg, pp. 252–262. Strobl/Blaschke/Griesebner, Heidelberg (2001)Google Scholar
  9. 9.
    Loyall, A.B.: Believable Agents, Ph.D. Thesis (Tech report CMU-CS-97-123), Carnegie Mellon University, Pittsburgh, Pennsylvania (1997)Google Scholar
  10. 10.
    Abraham, M.: Motivation and Personality, 2nd edn., Harper & Row (1970)Google Scholar
  11. 11.
    Moulin, B., Chaker, W., Perron, J., Pelletier, P., Hogan, J.: MAGS Project: Multi-agent geosimulation and crowd simulation. In: Kuhn, W., Worboys, M.F., Timpf, S. (eds.) COSIT 2003. LNCS, vol. 2825, pp. 151–168. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  12. 12.
    Perron, J., Moulin, B.: Un modèle de mémoire dans un système multi-agent de géo-simulation. Revue d’Intelligence Artificielle, Hermes (2004)Google Scholar
  13. 13.
    Raubal, M.: Agent-Based Simulation of human wayfinding. A perceptual model for unfamiliar building. PhD thesis. Vienna University of Technology. Faculty of Sciences and Informatics (2001)Google Scholar
  14. 14.
    Rymill, S.J., Dodgson, N.A.: A psychologically-based simulation of human behaviour. In: Lever, L., McDerby, M. (eds.) EG UK theory and Practice of Computer Graphics (2005)Google Scholar
  15. 15.
    Sung, M., Gleicher, M., Chenny, S.: Scalable behaviours for crowd simulation. Computer graphics Forum 23, 3 (2004)CrossRefGoogle Scholar
  16. 16.
    Tambe, M., Jones, R.M., Laird, J.E., Rosenbloom, P.S., Schwamb, K.: Building believable agents for simulation environments: Extended abstract. In: Bates, J. (ed.) Working Notes of the AAAI Spring Symposium on BelievableAgents, pp. 82–85. AAAI, Stanford (1994)Google Scholar
  17. 17.
    Ulicny, B., Thalmann, D.: Crowd Simulation for interactive virtual environments and VRtraining systems. In: Proceedings of Eurographics workshop on Animation and Simulation, pp. 163–170. Springer, Heidelberg (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Walid Ali
    • 1
    • 2
  • Bernard Moulin
    • 1
    • 2
  1. 1.Computer Science and Software Engineering DepartmentLaval UniversitySte FoyCanada
  2. 2.Research Center on GeomaticsLaval UniversitySte FoyCanada

Personalised recommendations