A Framework for Developing and Using Shared Mental Models in Human-Agent Teams
A Framework for Developing and Using Shared Mental Models in Human-Agent Teams
复制标题
在人类代理团队中开发和使用共享心理模型的框架
DOI：
10.1177/1555343416682891
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发表时间：
2017
影响因子：
2
通讯作者：
J. Adams
中科院分区：
文献类型：
--
作者：
Matthias Scheutz;S. DeLoach;J. Adams
来自心理学、人为因素、管理和组织科学以及其他相关领域的证据表明，在团队中工作的人使用共享的心理模型来表示和使用有关任务、设备、团队成员及其角色的相关信息。特别是，共享的心理模型用于与其他团队成员进行有效的交互，并跟踪目标，子目标，实现和计划状态以及其他团队相关因素的进展。虽然大部分关于共享心智模型的文献都集中在量化能够有效使用它们的团队的成功，但很少有关于操作它们的数据结构和过程的工作，这是操作共享心智模型所必需的。本文提出了第一个全面的正式和计算框架的基础上，从人类团队的结果，可用于实现共享的人工虚拟和机器人代理的心理模型。框架的形式部分指定了必要的数据结构和表示，而计算框架指定了必要的计算过程及其交互，以构建，更新和维护共享的心理模型。
Converging evidence from psychology, human factors, management and organizational science, and other related fields suggests that humans working in teams employ shared mental models to represent and use pertinent information about the task, the equipment, the team members, and their roles. In particular, shared mental models are used to interact efficiently with other team members and to track progress in terms of goals, subgoals, achieved and planned states, as well as other team-related factors. Although much of the literature on shared mental models has focused on quantifying the success of teams that can use them effectively, there is little work on the types of data structures and processes that operate on them, which are required to operationalize shared mental models. This paper proposes the first comprehensive formal and computational framework based on results from human teams that can be used to implement shared mental models for artificial virtual and robotic agents. The formal portion of the framework specifies the necessary data structures and representations, whereas the computational framework specifies the necessary computational processes and their interactions to build, update, and maintain shared mental models.
影响因子：
3.5
作者：
Keller, Johannes;Bless, Herbert;Kleinboehl, Dieter
通讯作者：
Kleinboehl, Dieter