DBLP:conf/aaai/GautierG93 +, KSL-93-06 + redirect page
Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering + Has identifier
Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering + Ksl tr id
Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering + Number
| Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering |
Bibtype
techreport
Has publishing details
1993
Has title
Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering
Has where published
KSL-93-06
Has year
1993
Title
Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering
Year
1993
Abstract
Generating explanations of device behavior … Generating explanations of device behavior is a long-standing goal of AI research in reasoning about physical systems. Much of the relevant work has concentrated on new methods for modeling and simulation, such as qualitative physics, or on sophisticated natural language generation, in which the device models are specially crafted for explanatory purposes. We show how two techniques from the modeling research—compositional modeling and causal ordering—can be effectively combined to generate natural language explanations of device behavior from engineering models. The explanations offer three advances over the data displays produced by conventional simulation software: (1) causal interpretations of the data, (2) summaries at appropriate levels of abstraction (physical mechanisms and component operating modes), and (3) query-driven, natural language summaries. Furthermore, combining the compositional modeling and causal ordering techniques allows models that are more scalable and less brittle than models designed solely for explanation. However, these techniques produce models with detail that can be distracting in explanations and would be removed in hand-crafted models (e.g., intermediate variables). We present domain-independent filtering and aggregation techniques that overcome these problems. n techniques that overcome these problems.
Address
Washington D.C. +
Author
Patrice O. Gautier and Thomas R. Gruber +
Has author
Patrice O. Gautier and Thomas R. Gruber +
Has identifier
Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering +
Institution
Knowledge Systems, AI Laboratory +
Ksl tr id
Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering +
Number
Generating Explanations of Device Behavior Using Compositional Modeling and Causal Ordering +
Process note
NO +
Categories KSL Technical Report +, Publication +, Technical Report +
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