Systems modeling language extension to support modeling of human-agent teams

Systems modeling language extension to support modeling of human-agent teams
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DOI:
10.1002/sys.21546
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发表时间:
2020-06-02
影响因子:
2
通讯作者:
Ford, Thomas C.
Ford, Thomas C.
中科院分区:
工程技术3区
文献类型:
--
作者:
Miller, Michael E.;McGuirl, John M.;Ford, Thomas C.

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我们提出了一个系统建模语言(SysML)的扩展,被称为“人类-代理团队建模语言”,和一个同伴的方法,被称为“人类-代理团队设计方法”,这是有用的设计和规范的团队组成的人类和人工代理系统内的互动。该语言和方法通过三步过程支持人-代理团队的分析和设计。首先,分析现有系统,以了解要实现的目标以及支持目标实现所需的角色和责任。同时,一个团队的人和人工代理合成,其中每个实体有能力在履行职责。第二,通过将代理能力与责任相匹配来将责任分配给代理。最后,通过对现有方法(称为相互依赖分析)的扩展应用,对设计进行了审查。这一步包括人类和人工代理之间的团队行为规范,以提高系统的鲁棒性。我们认为,所提出的语言和方法可以是有用的,在指定要求的人工代理,人类知识,和程序的要求,以及组件之间的关键互动多个人和人工代理组成的人类代理团队。
We propose a Systems Modeling Language (SysML) extension, referred to as the "Human-Agent Teaming Modeling Language," and a companion method, referred to as "Human-Agent Teaming Design Method," which are useful in the design and specification of teams comprised of humans and artificial agents which interact within a system. The language and method support the analysis and design of human-agent teams through a three-step process. First, an existing system is analyzed to understand the goals to be achieved as well as the roles and the responsibilities necessary to support goal attainment. Simultaneously, a team of humans and artificial agents are synthesized wherein each entity has capabilities useful in fulfilling the responsibilities. Second, responsibilities are allocated to agents by matching agent capabilities to responsibilities. Finally, the design is vetted through the application of an extension to an existing method referred to as Interdependence Analysis. This step includes the specification of teaming behaviors between humans and artificial agents to improve system robustness. We posit that the proposed language and method can be useful in specifying requirements for artificial agents, human knowledge, and procedure requirements, as well as components of critical interaction between multiple humans and artificial agents comprising a human-agent team.