Greater effects of mutual cooperation and defection on subsequent cooperation in direct reciprocity games than generalized reciprocity games: Behavioral experiments and analysis using multilevel models

Abstract

Reciprocity toward a partner’s cooperation is a fundamental behavioral strategy underlying human cooperation not only in interactions with familiar persons but also with strangers. However, a strategy that takes into account not only one’s partner’s previous action but also one’s own previous action—such as a win-stay lose-shift strategy or variants of reinforcement learning—has also been considered an advantageous strategy. This study investigated empirically how behavioral models can be used to explain the variances in cooperative behavior among people. To do this, we considered games involving either direct reciprocity (an iterated prisoner’s dilemma) or generalized reciprocity (a gift-giving game). Multilevel models incorporating inter-individual behavioral differences were fitted to experimental data using Bayesian inference. The results indicate that for these two types of games, a model that considers both one’s own and one’s partner’s previous actions fits the empirical data better than the other models. In the direct reciprocity game, mutual cooperation or defection—rather than relying solely on one’s partner’s previous actions—affected the increase or decrease, respectively, in subsequent cooperation. Whereas in the generalized reciprocity game, a weaker effect of mutual cooperation or defection on subsequent cooperation was observed.