Decision Infrastructure for Counterinsurgency Operational Planning (DICOP)

This paper describes a new Decision Infrastructure for Counterinsurgency Operational Planning (DICOP). DICOP facilitates the cognitive processes of the command team by providing a method for organizing relevant situational data visualizing and modeling operational factors, assessing uncertainty and...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Freedy, Elan, Lartigue, Lou, Chung, Lisa, Ratwani, Raj, Weltman, Gershon, Zanol, James, Pierce, Brian, Cohen, Marvin
Format: Report
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper describes a new Decision Infrastructure for Counterinsurgency Operational Planning (DICOP). DICOP facilitates the cognitive processes of the command team by providing a method for organizing relevant situational data visualizing and modeling operational factors, assessing uncertainty and risk, and identifying and planning courses of action that are likely to provide the greatest utility. DICOP is organized around three main components: Mission Analysis Mission Modeling; and Mission Planning. Mission Analysis provides a method for rapidly organizing and analyzing incoming intelligence and situational information. Mission Modeling provides a structure for constructing campaign models (lines of effort, objectives, and end states), using doctrinal templates, assessing the impact of situational factors, and associating intelligence information with the model. Mission Planning supports resource to task allocation, scheduling, and order generation. Initial positive evaluation by US Army command personnel has shown that DICOP is a powerful tool that fits the needs of the counterinsurgency planning team. Users highlighted three key cognitive features: (1) the ability to explicitly represent and manipulate operational factors in a modeling framework, (2) the ability to directly associate intelligence in support for or against those factors, and (3) numerical measures of utility and risk for different courses of action. The paper describes the DICOP cognitive rationale, its functional features, its initial evaluation, and the plans for further empirical evaluation in an operational environment. Presented at the 2011 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2011), 22-24 Feb, Miami Beach, FL.