Employing rich internal agent models of actors in large-scale socio-technical systems often results in scalability issues. The problem addressed in this paper is how to improve computational properties of a complex internal agent model, while preserving its behavioral properties. The problem is addressed for the case of an existing affective-cognitive decision making model instantiated for an emergency scenario. For this internal decision model an abstracted behavioral agent model is obtained, which ensures a substantial increase of the computational efficiency at the cost of approximately 1% behavioural error. The abstraction technique used can be applied to a wide range of internal agent models with loops, for example, involving mutual affective-cognitive interactions. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Sharpanskykh, A., & Treur, J. (2011). Abstraction of an affective-cognitive decision making model based on simulated behaviour and perception chains. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6589 LNCS, pp. 51–59). https://doi.org/10.1007/978-3-642-19656-0_8
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