面向人机交互的集成认知-工效架构：结合认知模型与人因工效学
Toward an~Integrated Cognitive--Ergonomic Architecture for~Human--Machine Interaction: Combining Cognitive Models with~Human Factors Ergonomics
浏览论文内容
中文总结 AI 辅助
该研究结合认知模型与HFE原理，合成定制架构解决动态环境下HMI复杂性，经工业机器人应用验证，增强HMI认知一致性并提供高风险环境下以人为中心界面的可扩展设计方法。
中文摘要 AI 辅助
本文提出一种集成方法，通过结合认知架构的理论基础与人因工效学（HFE）原理来建模人类能力。通过对已有的认知模型SOAR、ACT-R、LIDA和COCOM进行比较分析，我们合成了一种定制架构，旨在解决动态环境下人机交互（HMI）的复杂性。通过将该模型置于工效框架中，我们阐明了决策、技能获取和自适应行为的潜在机制，弥合了认知理论与应用系统设计之间的差距。我们的框架基于工业机器人应用的实证基础，在这些应用中，操作员专业知识、规范知识和实时反馈回路至关重要。所提出的架构不仅增强了人机交互系统的认知一致性，还为高风险环境下智能、以人为中心的界面设计提供了可扩展的方法。这项工作推进了对人类能力的理论理解，也推动了自适应、工效优化系统的实际实现。
英文摘要
This paper presents an integrated approach to modeling human competencies by combining the theoretical foundations of cognitive architectures with principles from Human Factors Ergonomics (HFE). Through a comparative analysis of established cognitive models-SOAR, ACT-R, LIDA, and COCOM-we synthesize a tailored architecture designed to address the complexities of human-machine interaction (HMI) in dynamic environments. By contextualizing this model within ergonomic frameworks, we elucidate the mechanisms underlying decision-making, skill acquisition, and adaptive behavior, bridging the gap between cognitive theory and applied system design. Our framework is empirically grounded in industrial robotics applications, where operator expertise, normative knowledge, and real-time feedback loops are critical. The proposed architecture not only enhances the cognitive alignment of HMI systems but also provides a scalable methodology for designing intelligent, human-centered interfaces in high-stakes environments. This work advances both the theoretical understanding of human competencies and the practical implementation of adaptive, ergonomically optimized systems.
发表机构
- Nantes Université（南特大学）
- École Centrale Nantes（南特中央理工学院）
- CNRS（法国国家科学研究中心）
- CETIM（法国机械工业技术中心）
- Université Rennes 2（雷恩第二大学）
机构由 AI 辅助整理，请以论文原文为准。
