People deciding between alternatives have at their disposal a toolbox containing both
compensatory strategies, which take into account all available attributes of those …

Several theories of cognition distinguish between strategies that differ in the mental effort
that their use requires. But how can the effort—or cognitive costs—associated with a strategy …

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice.
What are the neural mechanisms underlying decision strategy selection? The first goal of …

We propose a novel approach, which we call machine learning strategy identification
(MLSI), to uncovering hidden decision strategies. In this approach, we first train machine …

Objective: The present study used complex approximate and exact arithmetic computation
problems to dissociate the brain networks for strategy-based approximate computation and …

Real-life decision-making often involves combining multiple probabilistic sources of
information under finite time and cognitive resources. To mitigate these pressures, people …

Despite its unlimited capacity, not all visual information we encounter is encoded into visual
long-term memory. Traditionally, variability in encoding success has been ascribed to …

Large Language Models (LLMs) have achieved significant advancements, however, the
common learning paradigm treats LLMs as passive information repositories, neglecting their …

We propose a theoretical model that places attention at the center of mental time travel
(MTT) ability. This theory predicts that attention promotes a memory-based process that …

This paper identifies four attentional processes that increase efficiency and accuracy in
repeated lexicographic tasks using an instructed strategy approach. We propose a …