HCI International 2005 - The future of augmentation managers

T Diethe

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

In every Augmented Cognition (AugCog) application, where a closed-loop architecture is implemented, there is a requirement for a system that is responsible for the implementation of the strategies designed to mitigate the effects of excessive workload. The manner by which these mitigation strategies are implemented is likely to be platform specific, however several generic principles may be defined which enable the outputs of operator state gauges to be interpreted and acted upon.

In the simplest configuration an Augmentation Manager is designed to implement a single or number of mitigation strategies based on a single, high-level descriptor of operator state. In the initial implementation of the Tasking Interface Manager (TIM) in our Cognitive Cockpit (CogPit) the output of a single gauge, executive workload, was passed through a linear filter and a simple thresholding algorithm employed to trigger the implementation of a number of mitigation strategies. Whilst this showed some benefits during our first set of closed-loop trials, it is likely that this approach oversimplifies the problem. In particular, this approach did not take account of the complex relationship between mitigation strategies and state. In addition, any system that employs this, or similar techniques, will be purely reactive rather than proactive. Here we propose a multifaceted approach, in which the outputs of multiple gauges, operator state forecasting and context modeling together with a prediction of the effects of mitigation strategies on operator status will be used to drive the targeted application of a number of mitigation strategies. Achieving this will require a major engineering effort and carefully constructed empirical research.

Furthermore it is apparent that in order to make AugCog systems truly intelligent and adaptive, they will need to be able to monitor their own performance and adapt as necessary. Future systems will also need to be adaptive to the context in which they are operating, enabling the appropriate responses to unfamiliar contextual cues to be made. These occurrences should be stored in order to improve system operation under similar conditions should they arise again. This machine learning element to AugCog systems is probably the most underdeveloped area, but potentially could provide huge benefits to their long-term operational functionality.

Original languageEnglish
Title of host publicationFoundations of Augmented Cognition, Vol 11
EditorsDD Schmorrow
Place of PublicationMAHWAH
PublisherLawrence Erlbaum Associates, Publishers
Pages631-640
Number of pages10
ISBN (Print)0-8058-5806-7
Publication statusPublished - 2005
Event1st International Conference on Augmented Cognition held in Conjunction with the 11th International Conference on Human-Computer Interaction - Las Vegas, United Kingdom
Duration: 22 Jul 200527 Jul 2005

Conference

Conference1st International Conference on Augmented Cognition held in Conjunction with the 11th International Conference on Human-Computer Interaction
CountryUnited Kingdom
Period22/07/0527/07/05

Keywords

  • Augmentation Manager
  • closed-loop system
  • adaptive automation
  • Cognitive Cockpit
  • mitigation strategies
  • SYSTEMS

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