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Goal directed policy conflict detection and prioritisation: an empirical evaluation

Title	Goal directed policy conflict detection and prioritisation: an empirical evaluation
Author	Aphale, M. S., Norman, T. J., Şensoy, Murat
Publication Date:	2014
Publication Place	- Springer Science+Business Media
Subject	Policies, Norms, Conflict resolution
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-1-4503-2738-1
Record ID	f1f1bce3-eb03-4b25-9038-b8e56ff63a74
Library Location	Computer Science
Date	2014
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	We address the problem of developing effective automated reasoning support for the detection and resolution of conflicts between plans and policies (or norms). How automated reasoning mechanisms can effectively support human decision makers in this process is little understood. In this research, we have conducted experiments with human subjects to assess how effective these reasoning mechanisms are. We found that providing guidance to users regarding what problems to prioritise and highlighting related conflicts led to higher quality outcomes, and problems were successfully solved more rapidly.

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Özyeğin University

Goal directed policy conflict detection and prioritisation: an empirical evaluation

Author Aphale, M. S., Norman, T. J., Şensoy, Murat

Publication Date 2014

Publication Place - Springer Science+Business Media

Subject Policies, Norms, Conflict resolution

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-1-4503-2738-1

Record ID f1f1bce3-eb03-4b25-9038-b8e56ff63a74

Library Location Computer Science

Date 2014

Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Sample Text We address the problem of developing effective automated reasoning support for the detection and resolution of conflicts between plans and policies (or norms). How automated reasoning mechanisms can effectively support human decision makers in this process is little understood. In this research, we have conducted experiments with human subjects to assess how effective these reasoning mechanisms are. We found that providing guidance to users regarding what problems to prioritise and highlighting related conflicts led to higher quality outcomes, and problems were successfully solved more rapidly.