Modeling the impact of mental models on interactive decision-making and behavior

It is difficult for interactive systems to adapt to individual users due to the complex relationship between the user's mental model and observable behavior. This paper intro-duces a framework for making parameterized models that build on the assumption of computational rationality to formalize the link between mental models and interactive behavior. With two experiments, we illustrate how to infer the user's mental model from complex and limited observation through iterative inference and update, offering a computationally feasible approach for enhancing the understanding of the user. This work contributes to developing more intuitive and effective interactive systems in HCI and collaborative AI, emphasizing the need for a nuanced understanding of mental models and their impact on interaction.