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A Computational Model of Human Abductive Skill and its Acquisition
Abstract
Abduction is the process of constructing a plausible explanation for a set of observations. It is the fundamental type of reasoning in many complex tasks such as scientific discovery and diagnosis. This paper presents a mental-model theory of human abductive skill and its acquisition in which abduction is viewed as the sequential comprehension and integration of daU into a single situation model. Comprehension and integration are accomplished using satisficing search of multiple problem spaces. The model has been implemented in Soar and has been tested by comparing its predictions to those of human subjects. The experimental results show that the model can account for several important behavioral regularities, including power-law speed-up, bow the order of data presentation affects a response, deviation of responses from probability theory, and bow the task and domain characteristics affect a person's response.
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