# A quantum dynamic belief model to explain the interference effects of categorization on decision making

## TL;DR

This paper introduces a quantum dynamic belief model incorporating uncertainty to better predict how categorization influences decision making and causes interference effects, aligning with human cognitive processes.

## Contribution

A novel quantum dynamic belief model that accounts for uncertainty, providing a more succinct and effective explanation of categorization interference effects in decision making.

## Key findings

- The model successfully predicts interference effects observed in experiments.
- It outperforms existing models in explaining categorization-related decision anomalies.
- The approach aligns with human cognitive processes by incorporating uncertainty.

## Abstract

Categorization is necessary for many decision making tasks. However, the categorization process may interfere the decision making result and the law of total probability can be violated in some situations. To predict the interference effect of categorization, some model based on quantum probability has been proposed. In this paper, a new quantum dynamic belief (QDB) model is proposed. Considering the precise decision may not be made during the process, the concept of uncertainty is introduced in our model to simulate real human thinking process. Then the interference effect categorization can be predicted by handling the uncertain information. The proposed model is applied to a categorization decision-making experiment to explain the interference effect of categorization. Compared with other models, our model is relatively more succinct and the result shows the correctness and effectiveness of our model.