Affective Cognitive Model Based Interactive Decision-Making Approaches

The affective cognition of decision-makers plays an important role during the course of multi-objective decision making. If computers are enabled with human’s affective cognition, their ability and performances to supporting multi-objective decision-making could be significantly improved.In this thesis, a layered affective model merging personality, mood and emotional states is explicitly proposed, which describes the affective cognition of decision-makers in solving complex decision-making problems. This layered affective cognitive model promotes the creation of virtual human decision-makers who integrates human’s perceptual and rational characteristics. The virtual decision-makers instead of human ones participate in solving multi-objective optimization problems by means of interactive decision-making approaches. The main contributions of this paper are presented as follows.By combining personality, mood and emotional states a layered affective model is built. Subsequently, based on cognitive psychology principles and affective calculations, fuzzy reasoning methods are applied to evaluating the influence of external excitation signals on the emotion, resulting in an affective cognitive evaluation module. A combination of the two parts above helps formulate the layered affective cognition model which can be used to solve multi-objective decision-making problems through affective interactive decision-making termed as affective interactive decision-making approaches. As a result, the solutions of multi-objective decision-making problems can be attained free of human’s involvements direct. What’s more, the optimal solutions achieving from this model can fully reflect the subjective preferences of decision-makers. The affective interactive decision-making approach is applied to solving linear and nonlinear multi-objective decision-making problems, showing that the proposed approaches can be employed to substitute human decision-makers in the interactive decision-making, so that demonstrating the potential benefits.