For many years, scientists have sought to know how people make choices — whether or not we’re selecting what to eat for lunch or navigating high-stakes medical remedies. Conventional computational fashions of decision-making typically relaxation on fastened assumptions about how folks study from rewards and punishments. But these assumptions can battle to mirror the wealthy, adaptive methods during which people really behave.
In an effort to deal with this complexity, Dezfouli and colleagues launched a novel framework based mostly on recurrent neural networks (RNNs) of their paper: Fashions that find out how people study: The case of decision-making and its issues.
Their method goals to seize the nuanced processes behind human studying by coaching an RNN to mimic the subsequent motion a participant would absorb a decision-making job. Critically, the researchers examined this mannequin on each wholesome people and people dwelling with unipolar or bipolar despair.
By evaluating these teams, the examine not solely revealed the RNN’s capability to mannequin advanced behaviors extra precisely than conventional reinforcement-learning strategies, but additionally opened…