Reasoning about the Value of Decision Model Refinement: Methods and Application

Kim Leng Poh

Department of Engineering-Economic Systems
Stanford University
Stanford, California 94305

Eric Horvitz

Decision Theory & Adaptive Systems Group
Microsoft Research
Redmond, WA 98052

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Abstract:

We investigate the value of extending the completeness of a decision model along different dimensions of refinement. Specifically, we analyze the expected value of quantitative, conceptual, and structural refinement of decision models. We illustrate the key dimensions of refinement with examples. The analyses of value of model refinement can be used to focus the attention of an analyst or an automated reasoning system on extensions of a decision model associated with the greatest expected value.

Keywords: Control of reasoning, decision-theoretic metareasoning, bounded resources, model refinement

In: Proceedings of Ninth Conference on Uncertainty in Artificial Intelligence, Washington DC, July 1993. pages 174-182. Morgan Kaufmann: San Francisco.

Author Email: isepohkl@leonis.nus.sg, horvitz@microsoft.com