Humans Predict the Nash Equilibrium as an Outcome of a Multi-Agent Public Goods Game

Nash equilibrium is a well-established concept for predicting the outcome of a strategic game when the players are fully rational agents. While it is widely accepted that humans do not always behave as fully rational agents, our understanding of humans' prediction of the outcome of strategic games remains limited. This study attempts to bridge this gap by examining human subjects' prediction of the outcome of Public Goods in Networks (PGN) games. In this study, we explore participants' ability to predict PGN games' outcomes without prior knowledge of game theory or graph theory concepts. Therefore, we conduct a survey involving 96 participants, in which we request their predictions for PGN games' outcomes. Surprisingly, our findings indicate that participants, even in the absence of explicit knowledge regarding stability or equilibrium, tend to predict outcomes that align with a Nash equilibrium. This suggests that, in certain scenarios, the Nash equilibrium is in correspondence with human intuition and reasoning in strategic games. Finally, we examined two LLMs as 'participants', to test how often they propose outcomes that align with a Nash equilibrium. To much of our surprise, unlike humans, these models very rarely offered such predictions.