RESEARCH ON THE REGULATION OF MULTI-AGENT'S EMOTION BASED ON MULTI-AGENT'S HETEROGENEOUS GAME PREFERENCE AND BILATERAL PARTNER'S PREFERENCE
Authors: Xiao Hanjie , Bao Shuyan , Wu Liang , Tang Honglei , Wu Guosong , Zhou Jianhua , Xu Jianxin 
Published: July 2022

Background

The development of virtual enterprise is inseparable from the support of partners. Due to information asymmetry, the choice of virtual enterprise partners is blind, and simple matching formula is difficult to meet. At the same time, the psychology of the matching subject is based on the maximization of its own interests rather than the maximization of collective interests. There are interest contradictions and conflicts between subjects, and they may eventually fall into a “prisoner's dilemma”. Therefore, how to carry out the research on emotion regulation based on multi-agent heterogeneous game preference and bilateral partner preference is very important.

Research Objects and Methods

Aiming at the contradictions and interest conflicts between subjects in the process of virtual enterprise partner matching, combined with the basic characteristics of subject language preference evaluation, the game idea is introduced into the process of virtual enterprise partner bilateral matching analysis, a bilateral matching game model of heterogeneous multi-attribute preference and subjects' psychological behavior is proposed, and the influence of the changes of subjects' psychological behavior on the evolution law of bilateral matching game system is analyzed, The Nash equilibrium strategy of bilateral matching is discussed. In order to verify the impact of the algorithm on emotion, this study uses relevant scales to investigate. (1) Positive emotion scale. The Panas emotion scale developed by Watson et al. Is widely used to measure emotion. The scale includes two dimensions: positive emotion and negative emotion. There are 6 questions in this dimension, and Likert scores 5 points (1 means “very inconsistent”, 5 means “very consistent”, the same below). The Cronbach coefficient of this questionnaire is 0.90. (2) Motivation. The problem of measuring motivation is mainly the motivation scale compiled by Phan, which has 8 questions and is scored with Likert 5 points. (3) Social support scale. The scale is adapted from the social support scale compiled by Ye Yuemei et al. It has eight questions, using Likert's five points scoring method. Clonbach α the coefficient of the scale is 0.87. (4) Behavioral propensity scale. Propensity dimension in intention measurement. The scale has 6 questions, and Likert scores 5 points. The clonbach coefficient of the scale is 0.95.

Results

The results of case analysis show that the model can make full use of the multi-attribute preference information of heterogeneous subjects, describe the mechanism of psychological behavior affecting the evolution of game system, and help virtual enterprises match business partners; This has important value and significance for the establishment of virtual enterprises and their industrial agglomeration effect. In the influence process of cooperative anxiety, emotional response plays an intermediary role, psychological elasticity plays a regulatory role, and emotional response to life events plays an intermediary role. That is, the higher the psychological elasticity, the higher the excessive coping style of the game, and vice versa.

Conclusion

Various stable matching solutions can be obtained by solving the model, and the conclusion is more suitable for the matching decision-making process of both parties in the actual process, which makes the model can be applied to various scenarios, such as the selection of battery suppliers of new energy vehicles and smart phone screen suppliers, which has greater practical value and significance. It should be pointed out that there are some deficiencies in the setting conditions of the model method, mainly because some individuals in the group cooperate to form an alliance, so as to form a community of interests. In the process of game, the individual experience in the group is constrained by more conditions, which makes the results of the model deviate.

Acknowledgements

Zhejiang Provincial Natural Science Foundation (No. LQ20G010005), Zhejiang Provincial Statistical Science Research Project (NO. 21TJQN15) and Natural Science Fund Project of Huzhou City (No. 2018YZ13)