An Intelligent Agent Model with Awareness of Workflow Progress

F. Both, M. Hoogendoorn, A. van der Mee, J. Treur, M. de Vos

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

To support human functioning, ambient intelligent agents require knowledge about the tasks executed by the human. This knowledge includes design-time information like: (i) the goal of a task and (ii) the alternative ways for a human to achieve that goal, as well as run-time information such as the choices made by a human during task execution. In order to provide effective support, the agent must know exactly what steps the human is following. However, if not all steps along the path can be observed, it is possible that the agent cannot uniquely derive which path the human is following. Furthermore, in order to provide timely support, the agent must observe, reason, conclude and support within a limited period of time. To deal with these problems, this paper presents a generic focused reasoning mechanism to enable a guided selection of the path which is most likely followed by the human. This mechanism is based upon knowledge about the human and the workflow to perform the task. In order to come to such an approach, a reasoning mechanism is adopted in combination with the introduction of a new workflow representation, which is utilized to focus the reasoning process in an appropriate manner. The approach is evaluated by means of an extensive case study. © Springer Science+Business Media, LLC 2010.
LanguageEnglish
Pages498-510
JournalApplied Intelligence
Volume36
DOIs
Publication statusPublished - 2012

Fingerprint

Intelligent agents

Cite this

Both, F. ; Hoogendoorn, M. ; van der Mee, A. ; Treur, J. ; de Vos, M. / An Intelligent Agent Model with Awareness of Workflow Progress. In: Applied Intelligence. 2012 ; Vol. 36. pp. 498-510.
@article{26325e938b9c48b2a943f83fd8732f7c,
title = "An Intelligent Agent Model with Awareness of Workflow Progress",
abstract = "To support human functioning, ambient intelligent agents require knowledge about the tasks executed by the human. This knowledge includes design-time information like: (i) the goal of a task and (ii) the alternative ways for a human to achieve that goal, as well as run-time information such as the choices made by a human during task execution. In order to provide effective support, the agent must know exactly what steps the human is following. However, if not all steps along the path can be observed, it is possible that the agent cannot uniquely derive which path the human is following. Furthermore, in order to provide timely support, the agent must observe, reason, conclude and support within a limited period of time. To deal with these problems, this paper presents a generic focused reasoning mechanism to enable a guided selection of the path which is most likely followed by the human. This mechanism is based upon knowledge about the human and the workflow to perform the task. In order to come to such an approach, a reasoning mechanism is adopted in combination with the introduction of a new workflow representation, which is utilized to focus the reasoning process in an appropriate manner. The approach is evaluated by means of an extensive case study. {\circledC} Springer Science+Business Media, LLC 2010.",
author = "F. Both and M. Hoogendoorn and {van der Mee}, A. and J. Treur and {de Vos}, M.",
year = "2012",
doi = "10.1007/s10489-010-0273-9",
language = "English",
volume = "36",
pages = "498--510",
journal = "Applied Intelligence",
issn = "0924-669X",
publisher = "Springer Verlag",

}

An Intelligent Agent Model with Awareness of Workflow Progress. / Both, F.; Hoogendoorn, M.; van der Mee, A.; Treur, J.; de Vos, M.

In: Applied Intelligence, Vol. 36, 2012, p. 498-510.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - An Intelligent Agent Model with Awareness of Workflow Progress

AU - Both, F.

AU - Hoogendoorn, M.

AU - van der Mee, A.

AU - Treur, J.

AU - de Vos, M.

PY - 2012

Y1 - 2012

N2 - To support human functioning, ambient intelligent agents require knowledge about the tasks executed by the human. This knowledge includes design-time information like: (i) the goal of a task and (ii) the alternative ways for a human to achieve that goal, as well as run-time information such as the choices made by a human during task execution. In order to provide effective support, the agent must know exactly what steps the human is following. However, if not all steps along the path can be observed, it is possible that the agent cannot uniquely derive which path the human is following. Furthermore, in order to provide timely support, the agent must observe, reason, conclude and support within a limited period of time. To deal with these problems, this paper presents a generic focused reasoning mechanism to enable a guided selection of the path which is most likely followed by the human. This mechanism is based upon knowledge about the human and the workflow to perform the task. In order to come to such an approach, a reasoning mechanism is adopted in combination with the introduction of a new workflow representation, which is utilized to focus the reasoning process in an appropriate manner. The approach is evaluated by means of an extensive case study. © Springer Science+Business Media, LLC 2010.

AB - To support human functioning, ambient intelligent agents require knowledge about the tasks executed by the human. This knowledge includes design-time information like: (i) the goal of a task and (ii) the alternative ways for a human to achieve that goal, as well as run-time information such as the choices made by a human during task execution. In order to provide effective support, the agent must know exactly what steps the human is following. However, if not all steps along the path can be observed, it is possible that the agent cannot uniquely derive which path the human is following. Furthermore, in order to provide timely support, the agent must observe, reason, conclude and support within a limited period of time. To deal with these problems, this paper presents a generic focused reasoning mechanism to enable a guided selection of the path which is most likely followed by the human. This mechanism is based upon knowledge about the human and the workflow to perform the task. In order to come to such an approach, a reasoning mechanism is adopted in combination with the introduction of a new workflow representation, which is utilized to focus the reasoning process in an appropriate manner. The approach is evaluated by means of an extensive case study. © Springer Science+Business Media, LLC 2010.

U2 - 10.1007/s10489-010-0273-9

DO - 10.1007/s10489-010-0273-9

M3 - Article

VL - 36

SP - 498

EP - 510

JO - Applied Intelligence

T2 - Applied Intelligence

JF - Applied Intelligence

SN - 0924-669X

ER -