Two-armed bandit task

…of uncertainty, for instance, in a two-armed bandit task where arms have different reward distributions. Different frameworks have been suggested for representing probability distributions in t

…learning during goal-directed tasks remains to be determined. To investigate

Classical studies in reinforcement learning (RL) heavily rely on normative models of behavior, models that often stress interpretability over predictive capabilities. More recently, neural network models emerged as a descriptive modeling paradigm capable of high predictive power, however, with limited interpretation. To address these issues, we sought to augment the expressiveness of theoretically interpretable RL models with the high flexibility and predictive power of neural networks. Specifically, we introduce a novel framework whereby a neural network is trained to predict theoretically me

Reinforcement Learning studies how animals and humans adapt to their environment by learning from experience which actions maximize reward acquisition. Extant research has focused on situations where learners receive veridical reward-feedback. However, as social beings, much of the feedback we receive is provided by others. Critically, such feedback may be misleading because others might manipulate us based on their own –even if well-intended– interests. For example, a colleague might spare your feelings, expressing enthusiasm regarding your imminent Cosyne submission when, they actually find