People balance joint reward, fairness and complexity to develop social norms in a two-player game

Social norms are a hallmark of human social intelligence, yet the reasoning processes involved in norm formation have been difficult to capture with traditional modeling frameworks. We developed a computational model of norm formation as joint planning via theory-of-mind. The model is designed to capture the distinctively human ability to flexibly develop more complex norms in more complex situations, via simulation of joint decision-making with other agents over an extended time horizon. We evaluated the predictions of the model against participant interactions in a 2-player iterated decision-making task. Across 3 conditions our model captured the way participants balanced joint reward, fairness, and complexity when forming norms.