Dimitrije Marković

The paper introduces a joint model of choices and reaction times that integrates Bayesian decision making with sampling procedures to explain decision processes in cognitive tasks.

This study investigates how humans represent and use temporal structure in decision-making using a dynamic probabilistic learning task and computational modeling.

The paper presents a computational model of probabilistic inference over a hierarchy of time scales to solve the exploration-exploitation dilemma in cognitive control.

This paper introduces a hierarchical Bayesian model to explain how the brain balances habitual and goal-directed behavior through context-specific learning and probabilistic inference.