Emotions as a Vehicle for Rationality in Decision Making

Abstract

In this chapter, following a Network-Oriented Modeling approach, an adaptive temporal-causal network model is presented for decision making using valuing of action options based on predictive loops through feeling states. Hebbian learning is used for different types of connections in the adaptive network model. To assess the extent of rationality, a measure is introduced reflecting the environment’s behaviour. Simulation results and the extents of rationality of the different models over time are presented and analysed.