ACSEE: Antagonistic Crowd Simulation Model With Emotional Contagion and Evolutionary Game Theory

被引:29
|
作者
Li, Chaochao [1 ]
Lv, Pei [1 ]
Manocha, Dinesh [2 ]
Wang, Hua [1 ]
Li, Yafei [1 ]
Zhou, Bing [1 ]
Xu, Mingliang [1 ]
机构
[1] Zhengzhou Univ, Ctr Interdisciplinary Informat Sci Res, Zhengzhou 450000, Henan, Peoples R China
[2] Univ Maryland, Dept Comp Sci & Elect & Comp Engn, College Pk, MD 20742 USA
基金
中国国家自然科学基金;
关键词
Game theory; Games; Solid modeling; Force; Psychology; Market research; Biological system modeling; Group violence; emotional contagion; evolutionary game theory; PERSONALITY MODEL; CIVIL VIOLENCE; MULTIAGENT; FEAR;
D O I
10.1109/TAFFC.2019.2954394
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Antagonistic crowd behaviors are often observed in cases of serious conflict. Antagonistic emotions, which is the typical psychological state of agents in different roles (i.e., cops, activists, and civilians) in crowd violence scenes, and the way they spread through contagion in a crowd are important causes of crowd antagonistic behaviors. Moreover, games, which refers to the interaction between opposing groups adopting different strategies to obtain higher benefits and less casualties, determine the level of crowd violence. We present an antagonistic crowd simulation model (ACSEE), which is integrated with antagonistic emotional contagion and evolutionary game theories. Our approach models the antagonistic emotions between agents in different roles using two components: mental emotion and external emotion. We combine enhanced susceptible-infectious-susceptible (SIS) and game approaches to evaluate the role of antagonistic emotional contagion in crowd violence. Our evolutionary game theoretic approach incorporates antagonistic emotional contagion through deterrent force, which is modelled by a mixture of emotional forces and physical forces defeating the opponents. Antagonistic emotional contagion and evolutionary game theories influence each other to determine antagonistic crowd behaviors. We evaluate our approach on real-world scenarios consisting of different kinds of agents. We also compare the simulated crowd behaviors with real-world crowd videos and use our approach to predict the trends of crowd movements in violence incidents. We investigate the impact of various factors (number of agents, emotion, strategy, etc.) on the outcome of crowd violence. We present results from user studies suggesting that our model can simulate antagonistic crowd behaviors similar to those seen in real-world scenarios.
引用
收藏
页码:729 / 745
页数:17
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