Human-automated judgment learning: Applying interpersonal learning to investigate human interaction with alerting systems

Ellen J. Bass; Amy Pritchett

Human-automated judgment learning: Applying interpersonal learning to investigate human interaction with alerting systems

Ellen J. Bass
, Amy Pritchett

Aerospace Engineering

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

The application of human-automated judgement learning (HAJL) in interpersonal learning for investigating human interaction with alerting systems was discussed. HAJL models the impact of the alerting systems on the human judge by accounting for the initial conflict between them, the compromise of the human judge, and the adaptation that the human judge makes with respect to the automated judge and the environment. It was found that the unit of investigation was the parallel judgements of the human and automated judges in the uncertain environment.

Original language	English (US)
State	Published - Jan 1 2002
Event	Air Traffic Management for Commercial and Military Systems - Irvine, CA, United States Duration: Oct 27 2002 → Oct 31 2002

Other

Other	Air Traffic Management for Commercial and Military Systems
Country/Territory	United States
City	Irvine, CA
Period	10/27/02 → 10/31/02

All Science Journal Classification (ASJC) codes

Aerospace Engineering
Electrical and Electronic Engineering

Cite this

@conference{b5f2e4355ecb4090ab4c8626ff8fc3d1,

title = "Human-automated judgment learning: Applying interpersonal learning to investigate human interaction with alerting systems",

abstract = "The application of human-automated judgement learning (HAJL) in interpersonal learning for investigating human interaction with alerting systems was discussed. HAJL models the impact of the alerting systems on the human judge by accounting for the initial conflict between them, the compromise of the human judge, and the adaptation that the human judge makes with respect to the automated judge and the environment. It was found that the unit of investigation was the parallel judgements of the human and automated judges in the uncertain environment.",

author = "Bass, \{Ellen J.\} and Amy Pritchett",

year = "2002",

month = jan,

day = "1",

language = "English (US)",

note = "Air Traffic Management for Commercial and Military Systems ; Conference date: 27-10-2002 Through 31-10-2002",

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TY - CONF

T1 - Human-automated judgment learning

T2 - Air Traffic Management for Commercial and Military Systems

AU - Bass, Ellen J.

AU - Pritchett, Amy

PY - 2002/1/1

Y1 - 2002/1/1

N2 - The application of human-automated judgement learning (HAJL) in interpersonal learning for investigating human interaction with alerting systems was discussed. HAJL models the impact of the alerting systems on the human judge by accounting for the initial conflict between them, the compromise of the human judge, and the adaptation that the human judge makes with respect to the automated judge and the environment. It was found that the unit of investigation was the parallel judgements of the human and automated judges in the uncertain environment.

AB - The application of human-automated judgement learning (HAJL) in interpersonal learning for investigating human interaction with alerting systems was discussed. HAJL models the impact of the alerting systems on the human judge by accounting for the initial conflict between them, the compromise of the human judge, and the adaptation that the human judge makes with respect to the automated judge and the environment. It was found that the unit of investigation was the parallel judgements of the human and automated judges in the uncertain environment.

UR - https://www.scopus.com/pages/publications/18244429682

UR - https://www.scopus.com/pages/publications/18244429682#tab=citedBy

M3 - Paper

AN - SCOPUS:18244429682

Y2 - 27 October 2002 through 31 October 2002

ER -

Human-automated judgment learning: Applying interpersonal learning to investigate human interaction with alerting systems

Abstract

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All Science Journal Classification (ASJC) codes

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