Heterogeneous belief formation method based on BP neural network

¹ School of Automation, Huazhong University of Science and Technology, Wuhan 430074, P.R. China
² School of Management, Huazhong University of Science and Technology, Wuhan 430074, P.R. China
³ Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Wuhan 430074, P.R.China

^* Corresponding author: chenxi@mail.hust.edu.cn

Abstract

The BDI model has always been the focus of subject modeling research, which includes three kinds of thinking states of the rational subject: Belief, Desire and Intention. Belief is the cognition of agent to the world; it is a collection of environmental information, other agent information, and its own information that the agent has; and it is also the basis of the agent's thinking activity. Due to differences in the individual's living environment and experience, the formation of heterogeneous beliefs is an important issue in the BDI model study. This article divides individual belief set into two parts: knowledge belief and achievable belief. This article proposes an overall framework for the formation of individual heterogeneity beliefs: First, the individual's knowledge experience is modeled, and the empirical knowledge is structured and quantified into binary propositions; then the BP neural network learn and memory propositions of different combinations to form heterogeneous beliefs. Experiments show that this method can simulate the heterogeneity of individual beliefs caused by the individual's own experience, and can realize the belief generation mechanism of gradual information flow, limited attention and heterogeneous priors.