Recognition of user intentions for interface agents with variable order markov models

Abstract

A key aspect to study in the field of interface agents is the need to detect as soon as possible the user intentions. User intentions have an important role for an interface agent because they serve as a context to define the way in which the agents can collaborate with users. Intention recognition can be used to infer the user's intentions based on the observation of the tasks the user performs in a software application. In this work, we propose an approach to model the intentions the user can pursue in an application in a semi-automatic way, based on Variable-Order Markov models. We claim that with appropriate training from the user, an interface agent following our approach will be able both to detect the user intention and the most probable sequence of following tasks the user will perform to achieve his/her intention. © 2009 Springer Berlin Heidelberg.