Balancing precedent and mutual benefit in human coordination

Human societies rely on shared conventions that allow people to coordinate efficiently, from the conversational etiquette and the “rules of the road” to workplace roles and the handshake economy. To be effective, the conventions must be reliable, and yet also adaptable: when circumstances change, people must decide whether to follow established precedents or shift to new ways of coordinating. Most cognitive and computational models explain either how coordination equilibria emerge and persist through learning from past experience, or how agents generate novel strategies to maximize anticipated mutual benefit. How people arbitrate between these two modes of coordination remains poorly understood. Here we introduce a computational model and experimental paradigm to study this arbitration. In two preregistered experiments (n = 510; 30,420 choices), participants repeatedly solved coordination problems in which established precedents could be followed or abandoned as their efficiency declined. Our results quantify the conditions under which individuals and pairs transition from entrenched coordination equilibria to new shared solutions, revealing a dynamic trade-off between the reliability of precedent and the potential gains from innovation. These findings provide a unified account of how coordination remains both stable and adaptable, offering new insights into the evolution of conventions, norms, and institutions.