Abstract
With the increase of computing power and the development of user-friendly multi-agent simulation frameworks, social simulations have become increasingly realistic. However, most agent architectures in these simulations use simple reactive models. Indeed, cognitive agent architectures face two main obstacles: their complexity for the field-expert modeler, and their computational cost. In this paper, we propose a new cognitive agent architecture based on the BDI (Belief-Desire-Intention) paradigm integrated into the GAMA modeling platform and its GAML modeling language. This architecture was designed to be simple-to-use for modelers, flexible enough to manage complex behaviors, and with low computational cost. An experiment carried out with different profiles of end-users shows that the architecture is actually usable even by modelers who have little knowledge in programming and in Artificial Intelligence.
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This work is part of the ACTEUR (Spatial Cognitive Agents for Urban Dynamics and Risk Studies) research project funded by the French Research Agency (ANR).
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Taillandier, P., Bourgais, M., Caillou, P., Adam, C., Gaudou, B. (2017). A BDI Agent Architecture for the GAMA Modeling and Simulation Platform. In: Nardin, L., Antunes, L. (eds) Multi-Agent Based Simulation XVII. MABS 2016. Lecture Notes in Computer Science(), vol 10399. Springer, Cham. https://doi.org/10.1007/978-3-319-67477-3_1
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DOI: https://doi.org/10.1007/978-3-319-67477-3_1
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