Rationality for Adaptive Collective Decision Making Based on Emotion-Related Valuing and Contagion

Abstract. In this paper it is explored how adaptive collective decision making can be evaluated with respect to learning speed and rationality of the decisions. A collective decision model is presented based on interacting adaptive agents that learn from their experiences by a Hebbian learning mechanism. The decision making process makes use of emotionrelated valuing of decision options on the one hand based on predictive loops through feeling states, and on the other hand based on contagion. The resulting collective decision making process is analysed from the perspective of learning speed and rationality. Simulation results and the extent of rationality of the model over time are presented and analysed. It is shown how the collectiveness amplifies both learning speed and rationality of the decisions