Interactive acquisition of justifications: learning "why" by being told "what."
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abstract: In this paper I describe an approach to automated knowledge acquisition inwhich users specify desired system behavior by constructing justifications ofexamples. Justifications are explanations of why example behaviors areappropriate in given situations. I analyze the problem of acquiringjustifications, showing how current knowledge acquisition techniques are bestsuited for asking what-questions, while justifications are naturally viewed asanswers to why-questions. I sketch a new approach for acquiringjustifications that transforms why-questions into what-questions, borrowingthe sources of power of existing techniques. In this approach, usersconstruct justifications by selecting facts that specify what is relevant in asituation from a space of facts provided by the elicitation tool.Justifications are then used to create operational mappings from situations tointended outcomes. I show how the approach is applied to two differentknowledge acquisition problems: the acquisition of diagnostic strategy andthe acquisition of design rationale. I conclude by identifying commoncharacteristics of the two applications and discuss how their designdistributes the cognitive load between human and machines.
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| Abstract | In this paper I describe an approach to au … In this paper I describe an approach to automated knowledge acquisition inwhich users specify desired system behavior by constructing justifications ofexamples. Justifications are explanations of why example behaviors areappropriate in given situations. I analyze the problem of acquiringjustifications, showing how current knowledge acquisition techniques are bestsuited for asking what-questions, while justifications are naturally viewed asanswers to why-questions. I sketch a new approach for acquiringjustifications that transforms why-questions into what-questions, borrowingthe sources of power of existing techniques. In this approach, usersconstruct justifications by selecting facts that specify what is relevant in asituation from a space of facts provided by the elicitation tool.Justifications are then used to create operational mappings from situations tointended outcomes. I show how the approach is applied to two differentknowledge acquisition problems: the acquisition of diagnostic strategy andthe acquisition of design rationale. I conclude by identifying commoncharacteristics of the two applications and discuss how their designdistributes the cognitive load between human and machines. cognitive load between human and machines. |
| Author | Thomas R. Gruber + |
| Bibtype | techreport + |
| Institution | Knowledge Systems, AI Laboratory + |
| Key | KSL-91-17 + |
| Month | August + |
| Number | KSL-91-17 + |
| Tag | Computer science + |
| Title | Interactive Acquisition of Justifications: Learning "Why" by Being Told "What." + |
| Tr id | KSL-91-17 + |
| Year | 1991 + |
