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Implications of modern decision science for military decision-support systems / Paul K. Davis, Jonathan Kulick, Michael Egner.

By: Contributor(s): Material type: TextTextPublication details: Santa Monica, CA : Rand, Project Air Force, 2005.Description: 1 online resource (xxiv, 156 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780833040886
  • 083304088X
Subject(s): Genre/Form: Additional physical formats: Print version:: Implications of modern decision science for military decision-support systems.DDC classification:
  • 358.4/07/0973 22
LOC classification:
  • U393.5 .D37 2005eb
Online resources: Summary: Decision science concerns understanding human decisionmaking and methods and tools to assist it. The first concern includes the distinction between descriptive and prescriptive: how humans actually decide, versus how they should decide. Much of the early literature prescribed rational-analytic methods, such as embodied in systems analysis and policy analysis. The descriptive literature, however, has long noted that humans use heuristics (cognitive shortcuts), which are usually quite valuable, but which sometimes introduce unintended biases. Efforts have been made to improve decision support by "debiasing" the presentation of information. A newer literature on "naturalistic" decisionmaking, however, emphasizes the strengths of intuitive decisionmaking based on heuristics and questions the desirability of debiasing. Our study contrasts the schools of thought and suggests steps toward a synthesis. Ultimately, decision support should appeal to both the rational-analytic and the intuitive capabilities of the decisionmaker, with a balance of "cold" and story-based presentation of analysis and recommendations. The particular balance should depend on characteristics of the decision, the decision environment, and the decisionmaker. Our study also discusses new tools emerging for decision support, which include increasingly realistic models and simulations, such as virtual worlds, and new methods to help in the creative and imaginative aspects of strategic planning. Most important, we note modern methods, such as exploratory analysis, to encourage decisions and strategies that are flexible, adaptive, and robust so as to deal well with uncertainty.
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Electronic-Books Electronic-Books OPJGU Sonepat- Campus E-Books EBSCO Available

"Prepared for the United States Air Force, approved for Public release; distribution unlimited."

"MG-360-AF"--Page [4] cover.

Includes bibliographical references.

Decision science concerns understanding human decisionmaking and methods and tools to assist it. The first concern includes the distinction between descriptive and prescriptive: how humans actually decide, versus how they should decide. Much of the early literature prescribed rational-analytic methods, such as embodied in systems analysis and policy analysis. The descriptive literature, however, has long noted that humans use heuristics (cognitive shortcuts), which are usually quite valuable, but which sometimes introduce unintended biases. Efforts have been made to improve decision support by "debiasing" the presentation of information. A newer literature on "naturalistic" decisionmaking, however, emphasizes the strengths of intuitive decisionmaking based on heuristics and questions the desirability of debiasing. Our study contrasts the schools of thought and suggests steps toward a synthesis. Ultimately, decision support should appeal to both the rational-analytic and the intuitive capabilities of the decisionmaker, with a balance of "cold" and story-based presentation of analysis and recommendations. The particular balance should depend on characteristics of the decision, the decision environment, and the decisionmaker. Our study also discusses new tools emerging for decision support, which include increasingly realistic models and simulations, such as virtual worlds, and new methods to help in the creative and imaginative aspects of strategic planning. Most important, we note modern methods, such as exploratory analysis, to encourage decisions and strategies that are flexible, adaptive, and robust so as to deal well with uncertainty.

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