Abstraction of an Affective-Cognitive Decision Making Model Based on Simulated Behaviour and Perception Chains

ion of an Affective-Cognitive Decision Making Model based on Simulated Behaviour and Perception Chains Alexei Sharpanskykh and Jan Treur Vrije Universiteit Amsterdam, Department of Artificial Intelligence De Boelelaan 1081, 1081 HV Amsterdam, The Netherlands {sharp, treur}@few.vu.nl Abstract. Employing rich internal agent models of actors in large-scale sociotechnical 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. Employing rich internal agent models of actors in large-scale sociotechnical 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.