基于关联事件场的智能化仿真社会实验方法

Translated title of the contribution: Intelligent simulation social experiment method based on related event fields

Yulong Chen, Zhizhong Zhang, Lizhuang Ma, Shulan Ye, Mingang Chen

Research output: Contribution to journalArticlepeer-review

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.

Translated title of the contributionIntelligent simulation social experiment method based on related event fields
Original languageChinese (Traditional)
Pages (from-to)191-198
Number of pages8
JournalJournal of Graphics
Volume45
Issue number1
DOIs
StatePublished - 29 Feb 2024

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