Agent经济学：一种熵控制的多元对齐框架以防止自主智能体中的蜂群思维
Agent Economics: An Entropy-Controlled Pluralistic Alignment Framework for Preventing Artificial Hivemind in Autonomous Agents
AI总结：
提出行为协议框架(BPF)，通过心智化社会智能、多元对齐和可验证执行内核三个模块，在闭环架构中控制熵以保持策略多样性，提升自主智能体经济的稳定性、效率和可信度。
摘要：
本研究提出了行为协议框架（BPF），这是一个熵控制的多元对齐框架，旨在解决自主智能体经济中的两个关键挑战：由智能体间过度战略趋同引起的蜂群思维效应，以及自主决策过程中缺乏透明度。所提出的BPF由三个核心模块组成：基于心智理论的心智化社会智能（MbSI）、多元对齐（PA）和可验证执行内核（VEK）。这些模块有机地集成在一个闭环架构中，该架构控制着智能体行为从决策、执行到验证和反馈的整个生命周期。为了评估所提出的框架，将开发一个用Python实现的模拟环境和基于Streamlit的用户界面。通过实证实验，本研究旨在检验PA模块的熵控制机制能否有效保持智能体间的战略多样性并减轻集体趋同，同时VEK模块提供决策过程的全面且透明的审计追踪。预期结果将表明，所提出的框架能够同时增强自主智能体经济的稳定性、效率和可信度。因此，本研究为开发稳健、透明且可问责的智能体原生经济系统提供了一种实用方法。
英文摘要：
This study proposes the Behavioral Protocol Framework (BPF), an entropy-controlled pluralistic alignment framework designed to address two critical challenges in autonomous agent economies: the hivemind effect arising from excessive strategic convergence among agents and the lack of transparency in autonomous decision-making processes. The proposed BPF consists of three core modules: Mentalizing-based Social Intelligence (MbSI) grounded in Theory of Mind (ToM), Pluralistic Alignment (PA), and a Verifiable Execution Kernel (VEK). These modules are organically integrated within a closed-loop architecture that governs the entire lifecycle of agent behavior, from decision-making and execution to verification and feedback. To evaluate the proposed framework, a simulation environment implemented in Python and a Streamlit-based user interface will be developed. Through empirical experimentation, the study aims to examine whether the entropy-control mechanism of the PA module can effectively preserve strategic diversity among agents and mitigate collective convergence, while the VEK module provides a comprehensive and transparent audit trail of the decision-making process. The anticipated results are expected to demonstrate that the proposed framework can simultaneously enhance the stability, efficiency, and trustworthiness of autonomous agent economies. Consequently, this research offers a practical approach for developing robust, transparent, and accountable agent-native economic systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
