为自主智能体设计伦理情感调节框架，提升其学习中的道德决策能力。
Designing Ethical Learning for Agentic AI: Toegye Yi Hwang's Ethical Emotion Regulation Framework
- 基于朝鲜儒学思想构建五阶段情感调节架构
- 提出评估工具实现对道德情感对齐的系统化检验
- 适合研究智能体伦理、教育人工智能的学者与开发者
具备自主目标设定与主动干预能力的智能体系统，给学习环境中的道德-情感过程调控带来新挑战。现有框架通常将情绪视为被动反馈或参与度优化手段，忽略了在自主决策周期中进行规范性调控的需求。本文受朝鲜哲学家李滉（Toegye Yi Hwang）道德情感思想启发，提出一种面向智能体学习设计的伦理情感调节框架。该框架重构为五个阶段的体系结构，与智能体行为循环对齐，并提出各阶段的设计原则与场景分类。同时引入伦理情感反馈评估工具（EEFS Evaluation Instrument），支持对智能体系统在道德情感层面一致性进行系统化评估。
原文摘要 · Abstract (English)
Agentic AI systems capable of autonomous goal setting and proactive intervention introduce new challenges for regulating moral-emotional processes in learning environments. Existing frameworks typically treat emotion as reactive feedback or engagement optimization, overlooking the need for normative regulation across autonomous decision cycles.This paper proposes an ethical emotion regulation framework for agentic AI learning design inspired by Toegye Yi Hwang's moral-emotional philosophy. The Ethical Emotion Feedback System (EEFS) is reconstructed as a five-stage architecture aligned with agentic cycles, articulating stage-specific design principles and scenario classifications.An EEFS Evaluation Instrument is introduced to enable systematic assessment of moral-emotional alignment in agentic AI systems.
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