]> 2012-02-11T04:23:20-05:00 A Multiattribute Utility Approach to Inference Understandability and Explanation We describe research on the use of multiattribute utility models for tailoring expert-system inference and explanation to classes of users within alternative decision-making contexts. In particular, we introduce a formalization of automated explanation. We describe how useful explanations can be synthesized through the optimization of utility models that capture components of value in explanation. We discuss techniques for balancing the benefits of increased detail or completeness of analyses and explanations with the costs associated with accompanying increases in computational and cognitive complexity. We describe how the nature and optimal solution of such tradeoffs depend on the user and on the context. After introducing early work on user-specific multiattribute utility models in the PATHFINDER expert system for tissue-pathology diagnoses, we discuss current research on making complex reasoning more valuable through the explicit representation and manipulation of knowledge about multiple attributes of value in computational behavior. techreport 1987 A Multiattribute Utility Approach to Inference Understandability and Explanation KSL-87-28 1987 34 pages. A Multiattribute Utility Approach to Inference Understandability and Explanation 1987 Year Title NO Process note Number Note Ksl tr id Knowledge Systems, AI Laboratory Institution Has year Has where published Has title Has publishing details Has identifier Has author Bibtype Eric Horvitz Author Abstract KSL Technical Report Publication Technical Report