Cognitive modeling reveals menu search in both random and systematic
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Principles of mixed-initiative user interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
When policies are better than plans: decision-theoretic planning of recommendation sequences
Proceedings of the 6th international conference on Intelligent user interfaces
An evaluation of a multiple interface design solution for bloated software
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Using Bayesian Networks to Manage Uncertainty in Student Modeling
User Modeling and User-Adapted Interaction
Pre-sending Documents on the WWW: A Comparative Study
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Requirements Analysis for Customizable Software Goals-Skills-Preferences Framework
RE '03 Proceedings of the 11th IEEE International Conference on Requirements Engineering
Who's asking for help?: a Bayesian approach to intelligent assistance
Proceedings of the 11th international conference on Intelligent user interfaces
Exploring the design space for adaptive graphical user interfaces
Proceedings of the working conference on Advanced visual interfaces
A decision-theoretic approach to task assistance for persons with dementia
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A probabilistic mental model for estimating disruption
Proceedings of the 14th international conference on Intelligent user interfaces
A reference model for adaptive visualization systems
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: design and development approaches - Volume Part I
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The development of intelligent assistants has largely benefited from the adoption of decision-theoretic (DT) approaches that enable an agent to reason and account for the uncertain nature of user behaviour in a complex software domain. At the same time, most intelligent assistants fail to consider the numerous factors relevant from a human-computer interaction perspective. While DT approaches offer a sound foundation for designing intelligent agents, these systems need to be equipped with an interaction cost model in order to reason the impact of how (static or adaptive) interaction is perceived by different users. In a DT framework, we formalize four common interaction factors --- information processing, savings, visual occlusion, and bloat. We empirically derive models for bloat and occlusion based on the results of two users experiments. These factors are incorporated in a simulated help assistant where decisions are modeled as a Markov decision process. Our simulation results reveal that our model can easily adapt to a wide range of user types with varying preferences.