Extending Heuer ’ s Analysis of Competing Hypotheses Method to Support Complex Decision Analysis

نویسندگان

  • Michael Huhns
  • Jiangbo Dang
  • Hrishikesh Goradia
  • Jingshan Huang
چکیده

In this paper, we evaluate the Analysis of Competing Hypotheses (ACH) method using a normative Bayesian probabilistic framework. We describe the ACH method and present an example of how to use it to structure an analytic problem. We then show how to represent the same analytic problem using Bayesian networks and compare the result with that using the ACH method. We discuss how Bayesian networks generalize ACH tables and why the added generality might be important to the analyst for hypothesis management. Finally, we propose an approach for acquiring analytic models that interpret situations and for evaluating hypotheses, thereby combining the strengths of ACH and Bayesian networks.

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تاریخ انتشار 2005