Introduction to modeling and simulation
Proceedings of the 29th conference on Winter simulation
Spatial and Cognitive Simulation with Multi-agent Systems
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
Crowd simulation for interactive virtual environments and VR training systems
Proceedings of the Eurographic workshop on Computer animation and simulation
Proceedings of the 2008 Spring simulation multiconference
Multi-agent geosimulation in support to "what if" courses of action analysis
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
A New Classification of Collectives
Proceedings of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008)
A taxonomy of collective phenomena
Applied Ontology
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In this paper we present a simulation prototype of the customers' shopping behavior in a mall using a knowledge-based multiagent geosimulation approach. The shopping behavior in a shopping mall is performed in a geographic environment (a shopping mall) and is influenced by several shopper's characteristics (internal factors) and factors which are related to the shopping mall (external or situational factors). After identifying these factors from a large literature review we grouped them in what we called “dimensions”. Then we used these dimensions to design the knowledge-based agents' models for the shopping behavior simulation. These models are created from empirical data and implemented in the MAGS geosimulation platform. The empirical data have been collected from questionnaires in the Square One shopping mall in Toronto (Canada). After presenting the main characteristics of our prototype, we discuss how mall's managers of the Square One can use the Mall_MAGS prototype to make decisions about the mall spatial configuration by comparing different simulation scenarios. The simulation results are presented to mall's managers through a user-friendly tool that we developped to carry out data analysis.