A Computer Model of the Interpersonal Effect of Emotion Displayed in a Social Dilemma

The paper presents a computational model for decision-making in a social dilemma that takes into account the other party’s emotion displays. The model is based on data collected in a series of recent studies where participants play the iterated prisoner’s dilemma with agents that, even though following the same action strategy, show different emotion displays according to how the game unfolds. We collapse data from all these studies and fit, using maximum likelihood estimation, probabilistic models that predict likelihood of cooperation in the next round given different features. Model 1 predicts based on round outcome alone. Model 2 predicts based on outcome and emotion displays. Model 3 also predicts based on outcome and emotion but, considers contrast effects found in the empirical studies regarding the order with which participants play cooperators and non-cooperators. To evaluate the models, we replicate the original studies but, substitute the humans for the models. The results reveal that Model 3 best replicates human behavior in the original studies and Model 1 does the worst. The results, first, emphasize recent research about the importance of nonverbal cues in social dilemmas and, second, reinforce that people attend to contrast effects in their decision-making. Theoretically, the model provides further insight into how people behave in social dilemmas. Pragmatically, the model could be used to drive an agent that is engaged in a social dilemma with a human (or another agent).