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Affordances and Constraints of Intelligent Decision Support for Military Command and Control: Three Case Studies of Support Systems
Linköping University, Department of Computer and Information Science, MDALAB - Human Computer Interfaces. Linköping University, The Institute of Technology.
2011 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Möjligheter och begränsningar med intelligent  beslutsstöd i militär ledning : Tre fallstudier av teknikstöd (Swedish)
Abstract [en]

Researchers in military command and control (C2) have for several decades sought to help commanders by introducing automated, intelligent decision support systems. These systems are still not widely used, however, and some researchers argue that this may be due to those problems that are inherent in the relationship between the affordances of technology and the requirements by the specific contexts of work in military C2. In this thesis, we study some specific properties of three support techniques for analyzing and automating aspects of C2 scenarios that are relevant for the contexts of work in which they can be used.

The research questions we address concern (1) which affordances and constraints of these technologies are of most relevance to C2, and (2) how these affordances and limitations can be managed to improve the utility of intelligent decision support systems in C2. The thesis comprises three case studies of C2 scenarios where intelligent support systems have been devised for each scenario.

The first study considered two military planning scenarios: planning for medical evacuations and similar tactical operations. In the study, we argue that the plan production capabilities of automated planners may be of less use than their constraint management facilities. ComPlan, which was the main technical system studied in the first case study, consisted of a highly configurable, collaborative, constraint-management framework for planning in which constraints could be used either to enforce relationships or notify users of their validity during planning. As a partial result of the first study, we proposed three tentative design criteria for intelligent decision support: transparency, graceful regulation and event-based feedback.

The second study was of information management during planning at the operational level, where we used a C2 training scenario from the Swedish Armed Forces and the documents produced during the scenario as a basis for studying properties of Semantic Desktops as intelligent decision support. In the study, we argue that (1) due to the simultaneous use of both documents and specialized systems, it is imperative that commanders can manage information from heterogeneous sources consistently, and (2) in the context of a structurally rich domain such as C2, documents can contain enough information about domain-specific concepts that occur in several applications to allow them to be automatically extracted from documents and managed in a unified manner. As a result of our second study, we present a model for extending a general semantic desktop ontology with domain-specific concepts and mechanisms for extracting and managing semantic objects from plan documents. Our model adheres to the design criteria from the first case study.

The third study investigated machine learning techniques in general and text clustering in particular, to support researchers who study team behavior and performance in C2. In this study, we used material from several C2 scenarios which had been studied previously. We interviewed the participating researchers about their work profiles, evaluated machine learning approaches for the purpose of supporting their work and devised a support system based on the results of our evaluations. In the study, we report on empirical results regarding the precision possible to achieve when automatically classifying messages in C2 workflows and present some ramifications of these results on the design of support tools for communication analysis. Finally, we report how the prototype support system for clustering messages in C2 communications was conceived by the users, the utility of the design criteria from case study 1 when applied to communication analysis, and the possibilities for using text clustering as a concrete support tool in communication analysis.

In conclusion, we discuss how the affordances and constraints of intelligent decision support systems for C2 relate to our design criteria, and how the characteristics of each work situation demand new adaptations of the way in which intelligent support systems are used.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2011. , 154 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1381
Keyword [en]
Decision Support, planning, machine learning, information management, Command and Control
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-67630ISBN: 978-91-7393-133-5OAI: oai:DiVA.org:liu-67630DiVA: diva2:412065
Public defence
2011-06-17, Key 1, Hus Key, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2011-05-26 Created: 2011-04-20 Last updated: 2012-03-27Bibliographically approved
List of papers
1. Combining Technical and Human-Centered Strategies for Decision Support in Command and Control - The ComPlan Approach
Open this publication in new window or tab >>Combining Technical and Human-Centered Strategies for Decision Support in Command and Control - The ComPlan Approach
2008 (English)In: ISCRAM2008 Proceedings of the 5th International ISCRAM Conference / [ed] F. Fiedrich and B. Van de Walle, 2008, 504-515 p.Conference paper (Refereed)
Abstract [en]

ComPlan (A Combined, Collaborative Command and Control Planning tool) is an approach to providing knowledge-based decision support in the context of command and control. It combines technical research on automated planning tools with human-centered research on mission planning. At its core, ComPlan uses interconnected views of a planning situation to present and manipulate aspects of a scenario. By using domain knowledge flexibly, it presents immediate and directly visible feedback on constraint violations of a plan, facilitates mental simulation of events, and provides support for synchronization of concurrently working mission planners. The conceptual framework of ComPlan is grounded on three main principles from human-centered research on command and control: transparency, graceful regulation, and event-based feedback. As a result, ComPlan provides a model for applying a human-centered perspective on plan authoring tools for command and control, and a demonstration for how to apply that model in an integrated plan-authoring environment.

Keyword
Decision support, mixed-initiative planning, critiquing, cognitive systems engineering
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-42584 (URN)66339 (Local ID)66339 (Archive number)66339 (OAI)
Conference
5th International ISCRAM Conference, May 4-7, Washington, DC, USA
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-12-18Bibliographically approved
2. A Model for Document Processing in Semantic Desktop Systems
Open this publication in new window or tab >>A Model for Document Processing in Semantic Desktop Systems
2008 (English)In: Proceedings of the I-KNOW '08, the International Conference on Knowledge Management, Berlin, Heidelberg: Springer Verlag , 2008Conference paper (Refereed)
Abstract [en]

There is a significant gap between the services provided by dedicated information systems and general desktop systems for document communication and preparation. This situation is a serious knowledge-management problem, which often results in information loss, poor communication, and confusion among users. Semantic desktops promise to bring knowledge-based services to common desktop applications and, ultimately, to support knowledge management by adding advanced functionality to familiar computing environments. By custom tailoring these systems to different application domains, it is possible to provide dedicated services that assist users in combining document handling and communication with structured workflow processes and the services provided by dedicated systems. This paper presents a model for developing custom-tailored document processing for semantic-desktop systems. Our approach has been applied to the domain of military command and control, which as based on highly-structured document-driven processes. Key Words: semantic desktop, document-driven processes, semantic documents, planning

Place, publisher, year, edition, pages
Berlin, Heidelberg: Springer Verlag, 2008
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-42583 (URN)66319 (Local ID)66319 (Archive number)66319 (OAI)
Conference
I-KNOW '08, the International Conference on Knowledge Management, 3-5 September, Graz, Austria
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2011-05-26Bibliographically approved
3. Domain-specific knowledge management in a Semantic Desktop
Open this publication in new window or tab >>Domain-specific knowledge management in a Semantic Desktop
2009 (English)In: Proceedings of I-KNOW '09 9th International Conference on Knowledge Management and Knowledge Technologies / [ed] Klaus Tochtermann, 2009, 360-365 p.Conference paper (Refereed)
Abstract [en]

Semantic Desktops hold promise to provide intelligent information-management environments that can respond to users’ needs. A critical requirement for creating such environments is that the underlying ontology reflects the context of work properly. For specialized work domains where people deal with rich information sources in a context-specific manner, there may be a significant amount of domain-specific information available in text documents, emails and other domain-dependent data sources. We propose that this can be exploited to great effect in a Semantic Desktop to provide much more effective knowledge management. In this paper, we present extensions to an existing semantic desktop through content- and structure-based information extraction, domain-specific ontological extensions as well as visualization of semantic entities. Our extensions are justified by needs in strategic decision making, where domain-specific, well-structured knowledge is available in documents and communications but scattered across the desktop. The consistent and efficient use of these resources by a group of co-workers is critical to success. With a domain-aware semantic desktop, we argue that decision makers will have a much better chance of successful sense making in strategic decision making.

Keyword
semantic desktop, knowledge management, domain-specific ontology
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-56634 (URN)
Conference
9th International Conference on Knowledge Management and Knowledge Technologies 2-4 September, Graz, Austria
Available from: 2010-05-27 Created: 2010-05-27 Last updated: 2011-05-26Bibliographically approved
4. Message classification as a basis for studying command and control communication: an evaluation of machine learning approaches
Open this publication in new window or tab >>Message classification as a basis for studying command and control communication: an evaluation of machine learning approaches
2012 (English)In: Journal of Intelligent Information Systems, ISSN 0925-9902, E-ISSN 1573-7675, Vol. 38, no 2, 299-320 p.Article in journal (Refereed) Published
Abstract [en]

In military command and control, success relies on being able to perform key functions such as communicating intent. Most staff functions are carried out using standard means of text communication. Exactly how members of staff perform their duties, who they communicate with and how, and how they could perform better, is an area of active research. In command and control research, there is not yet a single model which explains all actions undertaken by members of staff well enough to prescribe a set of procedures for how to perform functions in command and control. In this context, we have studied whether automated classification approaches can be applied to textual communication to assist researchers who study command teams and analyze their actions. Specifically, we report the results from evaluating machine leaning with respect to two metrics of classification performance: (1) the precision of finding a known transition between two activities in a work process, and (2) the precision of classifying messages similarly to human researchers that search for critical episodes in a workflow. The results indicate that classification based on text only provides higher precision results with respect to both metrics when compared to other machine learning approaches, and that the precision of classifying messages using text-based classification in already classified datasets was approximately 50%. We present the implications that these results have for the design of support systems based on machine learning, and outline how to practically use text classification for analyzing team communications by demonstrating a specific prototype support tool for workflow analysis.

Place, publisher, year, edition, pages
Berlin: Springer, 2012
Keyword
Command and control – Classification, Exploratory sequential data analysis, Workflow mining, Random indexing, Text clustering
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-67227 (URN)10.1007/s10844-011-0156-5 (DOI)000302240800001 ()
Note

funding agencies|Swedish National Defense College||

Available from: 2011-04-06 Created: 2011-04-04 Last updated: 2012-05-03Bibliographically approved
5. Analysis tools in the study of distributed decision-making: a meta-study of command and control research
Open this publication in new window or tab >>Analysis tools in the study of distributed decision-making: a meta-study of command and control research
2012 (English)In: Cognition, Technology & Work, ISSN 1435-5558, E-ISSN 1435-5566, Vol. 14, no 2, 157-168 p.Article in journal (Refereed) Published
Abstract [en]

Our understanding of distributed decision making in professional teams and their performance comes in part from studies in which researchers gather and process information about the communications and actions of teams. In many cases, the data sets available for analysis are large, unwieldy and require methods for exploratory and dynamic management of data. In this paper, we report the results of interviewing eight researchers on their work process when conducting such analyses and their use of support tools in this process. Our aim with the study was to gain an understanding of their workflow when studying distributed decision making in teams, and specifically how automated pattern extraction tools could be of use in their work. Based on an analysis of the interviews, we elicited three issues of concern related to the use of support tools in analysis: focusing on a subset of data to study, drawing conclusionsfrom data and understanding tool limitations. Together, these three issues point to two observations regarding tool use that are of specific relevance to the design of intelligent support tools based on pattern extraction: open-endedness and transparency.

Place, publisher, year, edition, pages
Springer London, 2012
Keyword
Command and control, Text analysis, Interview study, Exploratory sequential data analysis
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-67228 (URN)10.1007/s10111-011-0177-4 (DOI)000310239500005 ()
Note

funding agencies|Swedish National Defense College||

Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2014-01-13Bibliographically approved
6. Automated text-based analysis for decision-making research
Open this publication in new window or tab >>Automated text-based analysis for decision-making research
2012 (English)In: Cognition, Technology & Work, ISSN 1435-5558, E-ISSN 1435-5566, Vol. 14, no 2, 129-142 p.Article in journal (Refereed) Published
Abstract [en]

We present results from a study on constructing and evaluating a support tool for the extraction of patterns in distributed decision -making processes, based on design criteria elicited from a study on the work process involved in studying such decision-making. Specifically, we devised and evaluated an analysis tool for C2 researchers who study simulated decision-making scenarios for command teams. The analysis tool used text clustering as an underlying pattern extraction technique and was evaluated together with C2 researchers in a workshop to establish whether the design criteria were valid and the approach taken with the analysis tool was sound. Design criteria elicited from an earlier study with researchers (open-endedness and transparency) were highly consistent with the results from the workshop. Specifically, evaluation results indicate that successful deployment of advanced analysis tools requires that tools can treat multiple data sources and offer rich opportunities for manipulation and interaction (open-endedness) and careful design of visual presentations and explanations of the techniques used (transparency). Finally, the results point to the high relevance and promise of using text clustering as a support for analysis of C2 data.

Place, publisher, year, edition, pages
Springer London, 2012
Keyword
Command and control, Text analysis, Exploratory sequential data analysis, Text clustering
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-67229 (URN)10.1007/s10111-010-0170-3 (DOI)000310239500003 ()
Note

The original publication is available at www.springerlink.com: Ola Leifler and Henrik Eriksson, Text-based Analysis for Command and Control Researchers: The Workflow Visualizer Approach, 2011, Cognition, Technology & Work. http://dx.doi.org/10.1007/s10111-010-0170-3 Copyright: Springer Science Business Media http://www.springerlink.com/

Available from: 2011-04-06 Created: 2011-04-04 Last updated: 2014-01-13Bibliographically approved

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