基于关联事件场的智能化仿真社会实验方法

doi:10.11996/JG.j.2095-302X.2024010191

图学学报 ›› 2024, Vol. 45 ›› Issue (1): 191-198.DOI: 10.11996/JG.j.2095-302X.2024010191

• 计算机图形学与虚拟现实 • 上一篇下一篇

基于关联事件场的智能化仿真社会实验方法

陈玉珑¹(), 张志忠², 马利庄¹(), 叶淑兰³, 陈敏刚⁴

1.上海交通大学电子信息与电气工程学院，上海 200240
2.华东师范大学计算机科学与技术学院，上海 200062
3.华东师范大学政治与国际关系学院，上海 200241
4.上海计算机软件技术开发中心，上海 201112

收稿日期:2023-07-20 接受日期:2023-10-31 出版日期:2024-02-29 发布日期:2024-02-29
通讯作者: 马利庄(1963-)，男，教授，博士。主要研究方向为计算机图形学、计算机视觉等。E-mail：lzma@sjtu.edu.cn
作者简介:
陈玉珑(1992-)，女，讲师, 博士后。主要研究方向为跨媒体智能与仿真实验。E-mail：llong_c@sjtu.edu.cn
基金资助:
国家自然科学基金委员会青年项目(62302296);国家自然科学基金委员会重大项目(61972157);上海市科委重大项目(2021SHZDZX0102)

Intelligent simulation social experiment method based on related event fields

CHEN Yulong¹(), ZHANG Zhizhong², MA Lizhuang¹(), YE Shulan³, CHEN Mingang⁴

1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2. School of Computer Science and Technology, East China Normal University, Shanghai 200062, China
3. School of Politics and International Relations, East China Normal University, Shanghai 200241, China
4. Shanghai Development Center of Computer Software Technology, Shanghai 201112, China

Received:2023-07-20 Accepted:2023-10-31 Online:2024-02-29 Published:2024-02-29
Contact: MA Lizhuang (1963-), professor, Ph.D. His main research interests cover graphic image, computer vision, etc. E-mail：lzma@sjtu.edu.cn
About author:
CHEN Yulong (1992-), lecturer, postdoctoral. Her main research interests cover cross-media intelligence and simulation experiments. E-mail：llong_c@sjtu.edu.cn
Supported by:
National Natural Science Foundation of China(62302296);National Natural Science Foundation of China(61972157);Shanghai Municipal Science and Technology Major Project(2021SHZDZX0102)

摘要/Abstract

摘要：

智能化进程正在迅速推动数字中国建设，不断改变相关社会和人文形态，同时引发了人工智能涉及的社会衍生风险等关键问题。在遵循社会伦理和隐私保护前提下，前瞻性探索新型人工智能社会实验模式，规范人工智能技术的发展，具有重要的现实意义。探讨了在特定社会实验环境下的事件场构建方式方法，以及人物、行为和场景三者的关联关系，基于数据和实验的社会化传导模式以及社会衍生效应进行预测。尝试通过前瞻性的虚拟仿真博弈实验，验证智能化仿真社会实验模式的有效性，为政府提供前瞻性的决策工具和智慧管理建议。

上海交通大学陈玉珑博士后和马利庄教授以及华东师范大学张志忠副研究员等针对基于关联事件场的智能化仿真社会实验方法，探讨在特定社会实验环境下的事件场构建方式方法，以及人物、行为和场景三者的关联关系，并基于数据和实验的社会化传导模式以及社会衍生效应进行预测。该方法尝试通过前瞻性的虚拟仿真博弈实验，验证智能化仿真社会实验模式的有效性，为政府提供前瞻性的决策工具和智慧管理建议。

关键词: 仿真实验, 事件场, 数字化身, 情感计算

Abstract:

The advancement of intelligence is rapidly promoting the development of digital China and continuously changing the relevant social and humanistic landscapes, while also bringing to the fore key issues such as socially derived risks involved in artificial intelligence (AI). It is of great practical significance to prospectively explore new models for AI social experimentation and regulate the development of AI technologies under the premise of adhering to social ethics and privacy protection. Methods for constructing event fields within specific social experimental settings were examined, alongside the interrelationships between characters, behaviors, and scenarios. Social transmission patterns and social derived effects were also predicted based on data and experimentation. Through prospective virtual simulation game experiments, an attempt was made to validate the effectiveness of an intelligent simulation social experiment model, explored the formation, discover innovative theoretical models and methods for new artificial intelligence social experiments, verify the role of event field models in intelligent simulation social experiments, and explore the social trans-mission patterns based on data and experiments as well as social derivative effects based on data and experiments for prediction, aiming to provide forward-looking decision-making tools and intelligent management suggestions for the government.

Key words: simulation experiments, event fields, digital avatars, emotional computing

中图分类号:

TP391

陈玉珑, 张志忠, 马利庄, 叶淑兰, 陈敏刚. 基于关联事件场的智能化仿真社会实验方法[J]. 图学学报, 2024, 45(1): 191-198.

CHEN Yulong, ZHANG Zhizhong, MA Lizhuang, YE Shulan, CHEN Mingang. Intelligent simulation social experiment method based on related event fields[J]. Journal of Graphics, 2024, 45(1): 191-198.

图/表 3

图1 化身个性化生成效果演示

Fig. 1 Avatar personalization generation effect demo

图2 人脸表情强度评估模型结构示意

Fig. 2 Schematic structure of the face expression intensity evaluation model

图3 虚拟仿真社会实验场景((a)虚拟医院场景；(b)虚拟超市场景)

Fig. 3 Virtual simulation social experiment scenes ((a) Virtual hospital scene; (b) Virtual supermarket scene)

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基于关联事件场的智能化仿真社会实验方法

Intelligent simulation social experiment method based on related event fields

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