Active Sensing Shapes Real-World Decision-Making through Dynamic Evidence Accumulation

This paper generalizes the Evidence Accumulation Model (EAM) to real-world contexts, investigating how active sensing through eye movements influences decision-making. It proposes a cognitive scheme that formalizes real-world evidence affordance and captures active sensing, offering a comprehensive account of human decision-making in dynamic environments.