报告详情
ParallelEarth An AI-Enabled Multi-Agent Framework for Digital Twin-Based Governance Simulation and Explainable Policy Analysis
编号：94
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更新：2026-11-10 16:45:08 浏览：8次
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报告开始：2026年11月20日 17:45（Asia/Kolkata）
报告时间：15min
所在会场：[S8] Signal Processing, RF and Communication Hardware/6G and Future Wireless Communication Systems [S8-1] Signal Processing, RF and Communication Hardware/6G and Future Wireless Communication Systems
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摘要
Methods based on historical data and expert judgment struggle to anticipate the long-term consequences of policy options. Digital Twins, Multi-Agent Systems (MAS), Decentralized Autonomous Organizations (DAOs) and Large Language Models (LLMs) are promising individually but rarely combined for governance simulation. This paper presents ParallelEarthDAO, a governance decision-support framework that combines a state-based governance simulation model (the Governance Digital Twin), a formally specified stakeholder-agent model with a deliberation protocol, a DAO-inspired decision rule and a traceable explanation layer in which an LLM verbalizes, but does not replace, a computed explanation trace. We specify how a proposal is represented, how agents evaluate and deliberate, how the simulation state evolves, how a weighted Governance Score is computed and how its sensitivity to normative weights is assessed, and demonstrate the pipeline on a controlled synthetic scenario implemented in the prototype; empirical validation is future work.
关键词
Digital Twin, Multi-Agent Systems, DAO Governance, eXplainable Artificial Intelligence, Large Language Models, Governance Simulation, Decision Support Systems, Blockchain.
报告人
Dhriti Vuppala
student sreenidhi institute of science and technology稿件作者
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重要日期
-
会议日期
11月20日
2026
至11月22日
2026
-
10月31日 2026
初稿截稿日期
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11月07日 2026
提前注册日期
-
11月22日 2026
注册截止日期
主办单位
United Societies of Science
承办单位
Pondicherry University
协办单位
IEEE Section
IEEE Madras Section
IEEE Madras Section
联系方式
- ICon INDIA 2026
- ic******@usssociety.org
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