Improved Human-Computer Interaction for Design of Complex Systems

未来复杂系统的设计，例如飞机、建筑和交通系统的设计，将由人类和人工智能(AI)系统的混合团队协作完成。这种合作的成功取决于人类和人工智能系统能够在多大程度上有效地相互沟通他们的目标、意图和行动计划。该奖项旨在改善人类和人工智能系统在设计此类系统时的沟通方式。特别是，研究人员将赋予智能设计代理通过语言和非语言沟通渠道向人类解释他们的行为和建议的能力。它还研究了人工智能系统如何使用机器人肢体语言来改进协同设计过程。这可能会对我们社会中从事系统设计的许多方面产生影响，包括建筑、医学、城市规划、工业设计和商业管理。此外，研究项目在其执行过程中提供了教育和推广的机会。该奖项的研究目标是通过赋予智能设计代理自我解释的能力，将人机联合设计建模为协作活动，并利用非语言渠道和具体化交互的使用来改善设计中的人机交流，从而实现复杂系统的混合主动性人机设计。从设计工具作为智能智能体的模型出发，基于人-机器人协作文献产生的知识，我们将为基于混合主动性人-智能体协作的工程设计新范式奠定基础。这一新范式的四个支柱是：(A)人类和设计主体之间共享的计划和意图的协调和相互配合，并将其分解为单独的主体计划和行动；(B)角色的动态分配和自主性的分级；(C)关于共享注意力和共同点的推理、产生和维持；以及(D)关于主体信念、意图和目标的语言和非语言渠道的整合。人体受试者的对照实验将被用来测试新框架和算法的有效性。如果成功，这项研究可以从根本上提高设计质量，并减少在具有国家重要性和社会高价值的复杂工程系统的设计过程中花费的资源，例如天气预报、气候监测、救灾或情报、监视和侦察的系统系统。这项研究还将对从事系统设计活动的工程学以外的领域产生更广泛的影响，包括建筑、医学、城市规划、工业设计和商业管理。

Future design of complex systems, for example, the design of aircraft, buildings, and transportation systems, will be done collaboratively by mixed teams of humans and artificial intelligence (AI) systems. The success of this collaboration depends on the degree to which the humans and the AI systems can effectively communicate with each other their goals, intentions and plans of actions. This award seeks to improve how humans and AI systems communicate when designing such systems. In particular, the investigators will give intelligent design agents the ability to provide explanations of their actions and suggestions to humans through both verbal and non-verbal communication channels. It also investigates how the AI system can use robotic body language to improve the collaborative design process. This has potential to have an impact on many aspects of our society which engage in system design, including architecture, medicine, urban planning, industrial design, and business management. Additionally, the research project provides opportunities for education and outreach during its execution.The research objective of this award is to enable mixed-initiative human-computer design of complex systems by giving intelligent design agents self-explaining abilities, modeling human-computer joint design as a collaborative activity, and leveraging the use of non-verbal channels and embodied interaction to improve human-machine communication in design. Starting from a model of design tools as intelligent agents, and based on the knowledge generated by the Human-Robot Collaboration literature, we will lay out the foundations of a new paradigm for engineering design based on mixed-initiative human-agent collaboration. The four pillars of this new paradigm are: (a) the coordination and meshing of shared plans and intentions between humans and design agents, and their resolution into individual agent plans and actions; (b) the dynamic allocation of roles and gradation of autonomy; (c) the reasoning about, generation, and maintenance of shared attention and common ground; and (d) the integration of verbal and nonverbal channels in communication about agent beliefs, intentions, and goals. Controlled experiments with human subjects will be used to test the effectiveness of the new framework and algorithms. If successful, this research can radically improve the quality of the designs and reduce the resources spent during the design process of complex engineering systems of national importance and high value to society such as systems-of-systems for weather forecasting, climate monitoring, disaster relief, or intelligence, surveillance, and reconnaissance. This research will also have broader impacts into areas outside of engineering that engage in system design activities, including architecture, medicine, urban planning, industrial design, and business management.