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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/75987


    Title: Simulating riot for virtual crowds with a social communication model
    Authors: Chao, Wei Ming;Li, Tsai-Yen
    趙偉銘;李蔡彥
    Contributors: 資科系
    Keywords: Agent based simulation;Collective behavior;Communication models;Computer Animation;Crowd density;Crowd Simulation;Individual agent;Initial position;Size symmetry;Social communication models;Social process;Virtual crowds;Animation;Communication;Computer simulation;Information theory;Intelligent agents;Multi agent systems;Autonomous agents
    Date: 2011
    Issue Date: 2015-06-22 13:49:00 (UTC+8)
    Abstract: In this work we attempt to build a communication model to simulate a large variety of collective behaviors in the course of riot formation for virtual crowd. The proposed crowd simulation system, IMCrowd, has been implemented with a multi-agent system in which each agent has a local perception and autonomous abilities to improvise their actions. The algorithms used in our communication model in IMCrowd are based heavily on sociology research. Therefore, the collective behaviors can emerge out of the social process such as emotion contagion and conformity effect among individual agents. We have conducted several riot experiments and have reported the details of the correlation between the severity of a riot and three predefined factors: the size of the crowd, relative size of the parties, and initial position distribution of the crowd. We have found that crowd density and party size symmetry do affect the number of victims at the end. However, the initial distribution of the two parties does not significantly influence the index (number of victims) at the end. © 2011 Springer-Verlag Berlin Heidelberg.
    Relation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 6922 LNAI, Issue PART 1, 2011, Pages 419-427, 3rd International Conference on Computational Collective Intelligence, ICCCI 2011; Gdynia; Poland; 21 September 2011 到 23 September 2011; 代碼 86602
    Data Type: conference
    DOI link: http://dx.doi.org/10.1007/978-3-642-23935-9_41
    DOI: 10.1007/978-3-642-23935-9_41
    Appears in Collections:[Department of Computer Science ] Proceedings

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