Interactive intelligent systems often suffer from a basic conflict between their computationally intensive nature and the need for responsiveness to a user This paper introduces the Interviewer/Reasoner model, which helps to reduce this conflict This model partitions an intelligent system into two asynchronous components The Interviewer's primary function is to gather data while providing an acceptable response time to the user The Reasoner does most of the symbolic computation for the system This paper describes the implementation of the model in both timesharing and personal workstat,ion environments, and uses the ONCOCIN system as an example The work described in t,his paper was carried out at Stanford University and was partly supported by the National Library of Medicine under program project grant LM-00395. The original idea for splitting the tasks of information gathering from reasoning in order to improve system response time was suggested by Ted Shortliffe and Chuck Clanton for the ONCOCIN project Thanks are due to Eric Schoen and Bill van Melle for help with the implementation, to Mark Stefik and Harold Brown for help in writing this paper, and to the rest of the ONCOCIN project members, including Carli Scott, Miriam Bischoff, Charlotte Jacobs, and Craig Tovey. An acceptable response time is needed both during system testing and to help insure end-user acceptability. During the normal course of development of an AI system there is substantial t,esting on real problems under the guidance of human experts whose time is usually valuable. Moreover, many end users (e.g., physicians) will simply refuse to use a system if they have to wait for a response.

Interactive intelligent systems often suffer from a basic conflict between their computationally intensive nature and the need for responsiveness end-user acceptability.

Interactive intelligent systems often suffer from a basic conflict between their computationally intensive nature and the need for responsiveness to a user. This paper introduces the Interviewer/Reasoner model, which helps to reduce this conflict. This model partitions an intelligent system into two asynchronous components. The Interviewer's primary function is to gather data while providing an acceptable response time to the user. The Reasoner does most of the symbolic computation for the system. This paper describes the implementation of the model in both timesharing and personal workstation environments, and uses the ONCOCIN system as an example.