Integrated models of learning and decision making in complex tasks

在自动化的帮助下，人们如何学会在复杂的工作系统中做出决策？该项目将开发人类学习和决策的计算模型，解释和预测与航空和国防等行业相关的复杂决策。它将研究人类如何学习使用自动化建议，学习如何影响记住执行计划（延迟）的行动，以及对学习和适应构成风险的因素。预期的结果是人为因素和认知心理学的重大理论进步，以及为工作设计提供信息的工具（例如，计算机接口、任务分配）和培训，有可能减少安全关键工作场所的人为错误。

How do people learn to make decisions in complex work systems when assisted by automation? This project will develop computational models of human learning and decision making that explain and predict complex decisions relevant to industries such as aviation and defence. It will examine how humans learn to use automated advice, how learning affects remembering to perform planned (deferred) actions, and factors that pose a risk to learning and adaptation. The expected outcome is a significant theoretical advance in human factors and cognitive psychology, and a tool for informing work design (e.g., computer interface, task allocation) and training, with the potential to reduce human error in safety-critical workplaces.