Abstract
Knowledge acquisition remains one of the primary constraints on the development of expert systems. A number of researchers have explored methods for allowing a machine learning system to assist a knowledge engineer in knowledge acquisition. In contrast, we are exploring methods for enabling an expert to directly interact with a machine learning system to collaborate during knowledge acquisition. We report recent extensions to our methodology encompassing a revised model of the role of machine learning in knowledge acquisition; techniques for communication between a machine learning system and a domain expert and novel forms of assistance that a machine learning system may provide to an expert.
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