Social psychologists attempt to explain how we interact by appealing to basic principles of
how we think. To make good on this ambition, they are increasingly relying on an …

Highlights•RL models have been applied to study the neural underpinnings of social
learning.•Past work has largely found neural correlates of observable, reward-predictive …

The central theme of this review is the dynamic interaction between information selection
and learning. We pose a fundamental question about this interaction: How do we learn what …

Human expression is open-ended, versatile, and diverse, ranging from ordinary language
use to painting, from exaggerated displays of affection to micro-movements that aid …

Humans are outstanding in their ability to cooperate with unrelated individuals, and
punishment–paying a cost to harm others–is thought to be a key supporting mechanism …

Designing reward functions for efficiently guiding reinforcement learning (RL) agents toward
specific behaviors is a complex task. This is challenging since it requires the identification of …

Those designing autonomous systems that interact with humans will invariably face
questions about how humans think and make decisions. Fortunately, computational …

From the earliest years of our lives, humans use language to express our beliefs and
desires. Being able to talk to artificial agents about our preferences would thus fulfill a …

Humans use punishment to influence each other's behavior. Many current theories presume
that this operates as a simple form of incentive. In contrast, we show that people infer the …

Abstract Theory of mind enables an observer to interpret others' behavior in terms of
unobservable beliefs, desires, intentions, feelings, and expectations about the world. This …