Antonios Nasioulas

Biased processing of multiple outcomes in human reinforcement learning: evidence from computational modeling and eye-tracking

In many circumstances, choices result in multiple simultaneous outcomes, all of which should be integrated to optimally update reward expectation. Yet, to date, empirical investigations of reinforcement learning have mostly focused on situations where choices deliver only one outcome at a time. To understand how humans...