Combining Decision-Making Theories With a Cognitive Theory for Intelligent Help: A Comparison

Abstract

This research investigates the novel combination of multicriteria decision-making theories with a cognitive theory called human plausible reasoning (HPR) to provide personalized assistance via graphical user interfaces (GUIs). A GUI called intelligent file manipulator (IFM) helps with organizing computer file storage. The system reasons about user actions, goals, plans, and possible errors and offers automatic assistance in case of a problematic situation. Three multicriteria decision-making theories [simple additive weighting, multiattribute utility theory, and data envelopment analysis] were adapted, implemented, and combined with HPR, in turn. This process resulted in three different versions of IFM that were evaluated. The protocols of 30 users of different levels of expertise were provided to the system with each of the versions and to ten human experts. The responses of the experts and the different versions of the system were compared. The evaluation revealed that decision-making theories can increase control in an intelligent user interface. They can be combined with a cognitive theory like HPR. There was 66–81% compatibility of the different systems’ responses to the proposals of the majority of experts. All decision-making theories were better in simulating the human experts’ reasoning when there was unanimity of the human experts’ opinion. In such cases, there was 68–84% compatibility of the different systems’ responses to the experts’ proposals. This research supports that HPR could successfully be completed by a multicriteria decision-making theory, and such combination can be effectively used for providing personalized help in GUIs.