A Scalable Theory of Behavior Composition for Practical Engineering Models of Human Performance

用于人类绩效实际工程模型的可扩展行为构成理论

• 批准号: DP0666772
• 负责人: Prof Roger Remington
• 金额: $ 63.79万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2006
• 资助国家: 澳大利亚
• 起止时间: 2006-10-01 至 2011-09-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0666772
• 关键词: Scalable; Theory; Behavior; Composition; Practical

Minimizing human error and maximizing human performance is a major design goal in safety critical systems. The development of methods for affordable human performance modeling has widespread applicability for evaluating user-system interfaces. The compositional method explored here has been shown to make accurate predictions reduce model development time by an order of magnitude. Large safety critical applications, such as military or air traffic control systems, would benefit greatly. The proposed work tests whether the compositional methods will scale to more complex domains. The work will be coordinated with Australian industry, academia, and government research efforts.

最小化人为错误和最大化人的性能是安全关键系统的主要设计目标。开发经济实惠的人的性能建模方法具有广泛的适用性，用于评估用户-系统界面。这里探索的组合方法已被证明可以进行准确的预测，减少模型开发时间的数量级。大型安全关键应用，如军事或空中交通管制系统，将大大受益。拟议的工作测试是否组合方法将扩展到更复杂的领域。这项工作将与澳大利亚工业界、学术界和政府的研究工作协调进行。