Design Requirements for Effective Hybrid Decision Making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

Design requirements for effective hybrid decision making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

How do principles for human-centred automation apply to Disruption Management Decision Support?

While automation of signal and route setting is routine, the use of automation or decision support in disruption management processes is far less common. Such support offers significant advantages in optimising re-planning of both timetable and resources (crew and rolling stock), and has value in offering a 'shared view' of re-planning across the many actors manage disruption. If this vision is to be realised, however, disruption management decision support and automation must adhere to proven principles for effective human-agent cooperation. This paper synthesises data from a programme of work to understand user requirements for automated disruption support tools. It then compares these outputs with two frameworks for human-centred automation - one general (Klein et al's [2004] ten challenges for automation) and one transport specific (Balfe et al’s [2012] principles for transport automation). Emergent design requirements include the need for iterative modification of rescheduling parameters throughout a disruption, visibility of the reasoning behind options, accountability remaining in the hands of disruption controllers, and the need for the automated disruption support tools to take a multi-dimensional view of disruption that varies depending on the event encountered. The paper reflects on the practical utility of high-level design principles for automated disruption support tools

How do principles for human-centred automation apply to Disruption Management Decision Support?

While automation of signal and route setting is routine, the use of automation or decision support in disruption management processes is far less common. Such support offers significant advantages in optimising re-planning of both timetable and resources (crew and rolling stock), and has value in offering a 'shared view' of re-planning across the many actors manage disruption. If this vision is to be realised, however, disruption management decision support and automation must adhere to proven principles for effective human-agent cooperation. This paper synthesises data from a programme of work to understand user requirements for automated disruption support tools. It then compares these outputs with two frameworks for human-centred automation - one general (Klein et al's [2004] ten challenges for automation) and one transport specific (Balfe et al’s [2012] principles for transport automation). Emergent design requirements include the need for iterative modification of rescheduling parameters throughout a disruption, visibility of the reasoning behind options, accountability remaining in the hands of disruption controllers, and the need for the automated disruption support tools to take a multi-dimensional view of disruption that varies depending on the event encountered. The paper reflects on the practical utility of high-level design principles for automated disruption support tools

Design requirements for effective hybrid decision making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

How do principles for human-centred automation apply to Disruption Management Decision Support?

While automation of signal and route setting is routine, the use of automation or decision support in disruption management processes is far less common. Such support offers significant advantages in optimising re-planning of both timetable and resources (crew and rolling stock), and has value in offering a 'shared view' of re-planning across the many actors manage disruption. If this vision is to be realised, however, disruption management decision support and automation must adhere to proven principles for effective human-agent cooperation. This paper synthesises data from a programme of work to understand user requirements for automated disruption support tools. It then compares these outputs with two frameworks for human-centred automation - one general (Klein et al's [2004] ten challenges for automation) and one transport specific (Balfe et al’s [2012] principles for transport automation). Emergent design requirements include the need for iterative modification of rescheduling parameters throughout a disruption, visibility of the reasoning behind options, accountability remaining in the hands of disruption controllers, and the need for the automated disruption support tools to take a multi-dimensional view of disruption that varies depending on the event encountered. The paper reflects on the practical utility of high-level design principles for automated disruption support tools

Measuring collaborative emergent behavior in multi-agent reinforcement learning

Multi-agent reinforcement learning (RL) has important implications for the future of human-agent teaming. We show that improved performance with multi-agent RL is not a guarantee of the collaborative behavior thought to be important for solving multi-agent tasks. To address this, we present a novel approach for quantitatively assessing collaboration in continuous spatial tasks with multi-agent RL. Such a metric is useful for measuring collaboration between computational agents and may serve as a training signal for collaboration in future RL paradigms involving humans.Comment: 1st International Conference on Human Systems Engineering and Design, 6 pages, 2 figures, 1 tabl

Making intelligent systems team players: Overview for designers

This report is a guide and companion to the NASA Technical Memorandum 104738, 'Making Intelligent Systems Team Players,' Volumes 1 and 2. The first two volumes of this Technical Memorandum provide comprehensive guidance to designers of intelligent systems for real-time fault management of space systems, with the objective of achieving more effective human interaction. This report provides an analysis of the material discussed in the Technical Memorandum. It clarifies what it means for an intelligent system to be a team player, and how such systems are designed. It identifies significant intelligent system design problems and their impacts on reliability and usability. Where common design practice is not effective in solving these problems, we make recommendations for these situations. In this report, we summarize the main points in the Technical Memorandum and identify where to look for further information

The Impact of Coordination Quality on Coordination Dynamics and Team Performance: When Humans Team with Autonomy

abstract: This increasing role of highly automated and intelligent systems as team members has started a paradigm shift from human-human teaming to Human-Autonomy Teaming (HAT). However, moving from human-human teaming to HAT is challenging. Teamwork requires skills that are often missing in robots and synthetic agents. It is possible that adding a synthetic agent as a team member may lead teams to demonstrate different coordination patterns resulting in differences in team cognition and ultimately team effectiveness. The theory of Interactive Team Cognition (ITC) emphasizes the importance of team interaction behaviors over the collection of individual knowledge. In this dissertation, Nonlinear Dynamical Methods (NDMs) were applied to capture characteristics of overall team coordination and communication behaviors. The findings supported the hypothesis that coordination stability is related to team performance in a nonlinear manner with optimal performance associated with moderate stability coupled with flexibility. Thus, we need to build mechanisms in HATs to demonstrate moderately stable and flexible coordination behavior to achieve team-level goals under routine and novel task conditions.Dissertation/ThesisDoctoral Dissertation Engineering 201