Adolescence is a period of life during which peers play a pivotal role in decision-making. The narrative of social influence during adolescence often revolves around risky and maladaptive decisions, like driving under the influence, and using illegal substances ( Steinberg, 2005 ). However, research has also shown that social influence can lead to increased prosocial behaviors ( Van Hoorn et al., 2017 ) and a reduction in risk-taking ( Braams et al., 2019 ). While many studies support the notion that adolescents are more sensitive to peer influence than children or adults, the developmental processes that underlie this sensitivity remain poorly understood. We argue that one important reason for this lack of understanding is the absence of precisely formulated models. To make a first step toward formal models of social influence during adolescence, we first identify three prominent verbal models of social influence in the literature: (1) social motivation, (2) reward sensitivity, and (3) distraction. We then illustrate how these can be translated into formal models, and how such formal models can inform experimental design and help identify developmental processes. Finally, by applying our formal models to existing datasets, we demonstrate the usefulness of formalization by synthesizing different studies with seemingly disparate results. We conclude with a discussion on how formal modeling can be utilized to better investigate the development of peer influence in adolescence.

Humans and other animals are capable of inferring never-experienced relations (for example, A > C) from other relational observations (for example, A > B and B > C). The processes behind such transitive inference are subject to intense research. Here we demonstrate a new aspect of relational learning, building on previous evidence that transitive inference can be accomplished through simple reinforcement learning mechanisms. We show in simulations that inference of novel relations benefits from an asymmetric learning policy, where observers update only their belief about the winner (or loser) in a pair. Across four experiments (n = 145), we find substantial empirical support for such asymmetries in inferential learning. The learning policy favoured by our simulations and experiments gives rise to a compression of values that is routinely observed in psychophysics and behavioural economics. In other words, a seemingly biased learning strategy that yields well-known cognitive distortions can be beneficial for transitive inferential judgements.

Adolescents are often described as a strange and different species that behaves like no other age group, typical behaviours being excessive risk-taking and sensitivity to peer influence. Different theories of adolescent behaviour attribute this to different internal mechanisms like undeveloped cognitive control, higher sensation-seeking or extraordinary social motivation. Many agree that some of adolescent risk-taking behaviour is adaptive. Here we argue that to understand adolescent risktaking, and why it may be adaptive, research needs to pay attention to the adolescent environments' structure and view adolescents as learning and exploring agents in it. We identify three unique aspects of the adolescent environment: 1) the opportunities to take risks are increased significantly, 2) these opportunities are novel and their outcomes uncertain, and 3) peers become more important. Next, we illustrate how adolescent risk-taking may emerge from learning using agent-based modelling, and show that a typical inverted-U shape in risk-taking may emerge in absence of a specific adolescent motivational drive for sensation-seeking or sensitivity to social information. The simulations also show how risky exploration may be necessary for adolescents to gain long-term benefits in later developmental stages and that social learning can help reduce losses. Finally, we discuss how a renewed ecological perspective and the focus on adolescents as learning agents may shift the interpretation of current findings and inspire future studies.