A User Modeling Approach to Determining System Initiative in Mixed-Initiative AI Systems
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In this paper, we address the problem of providing guidelines to designers of mixed-initiative artificial intelligence systems, which specify when the system should take the initiative to solicit further input from the user, in order to carry out a problem solving task. We first present a utility-based quantitative framework which is dependent on modeling: whether the user has the knowledge the system is seeking, whether the user is willing to provide that knowledge and whether the user would be capable of understanding the request for information from the system. Examples from the application of sports scheduling are included. We also discuss a qualitative version of the model, for applications with sparse data. This paper demonstrates a novel use for user models, one in which the system does not simply alter its generation based on the user model, but in fact makes a user-specific decision about whether to interact at all.
Keywordsmixed-initiative systems dialogue exploiting user models to adapt interaction interactive scheduling clarification tailoring generation
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