What place should formal or computational methods occupy in social psychology? We consider this question in historical perspective, survey the current state of the field, introduce the several new contributions to this special issue, and reflect on the future.

A key benefit of Bayesian reasoning is that it stipulates how to optimally integrate unreliable sources of information. The authors present evidence that humans use Bayesian inference to determine how much to trust advice from another person, based on information about that person's knowledge and strategy.

According to rational pedagogy models, learners take into account the way in which teachers generate evidence, and teachers take into account the way in which learners assimilate that evidence. The authors develop a framework for integrating rational pedagogy into models of active exploration, in which agents can take actions to influence the evidence they gather from the environment. The key idea is that a single agent can be both teacher and learner.

An important, but relatively neglected, aspect of human theory of mind is emotion inference: understanding how and why a person feels a certain why is central to reasoning about their beliefs, desires and plans. The authors review recent work that has begun to unveil the structure and determinants of emotion inference, organizing them within a unified probabilistic framework.

The social environment influences what information individuals sample: people are often exposed to alternatives that are popular. This can systematically change an individual's evaluation of an alternative if she had previously been avoiding it due to a negative evaluation. The authors show that social exposure can have positive or negative effects on evaluation, depending on how popularity and prior evaluations interact. This theory was supported by a large-scale analysis of data from a hotel chain.

What are the conditions under which groups of agents will perform well across multiple tasks? The author establishes a set of “alignment conditions” that enforce identity of beliefs and desires across agents. These conditions are necessary and sufficient for ensuring that a multiagent system behaves as if controlled by a rational centralized controller. Several widely observed social phenomena can be understood as facilitating the alignment conditions.

Why do people enter devoted relationships when they can continue looking for better partners? The “strategic ignorance” account holds that remaining ignorant about alternative partners is a signal that you are a high-quality partner. Despite this intuition, the authors show that evolution favors a “look while allowing your partner to look” strategy, unless the costs of being rejected by a looking partner are extremely high. Thus, the origins of love must be found elsewhere.

The authors explore the interfaces between different dimensions of moral cognition, bridging economic, Bayesian and reinforcement learning perspectives. The human aversion to harming others cuts across these different interfaces, influencing decisions, judgments, and inferences about morality.

In rebellion against low-dimensional (e.g., two-factor) theories in psychology, the authors make the case for high-dimensional theories. This change in perspective requires a shift towards a focus on computation and quantitative reasoning.