Active sampling as an information seeking strategy in primate vocal interactions

Active sensing is a behavioral strategy for exploring the environment. In this study, we show that contact vocal behaviors can be an active sensing mechanism that uses sampling to gain information about the social environment, in particular, the vocal behavior of others. With a focus on the real-time vocal interactions of marmoset monkeys, we contrast active sampling to a vocal accommodation framework in which vocalizations are adjusted simply to maximize responses. We conduct simulations of a vocal accommodation and an active sampling policy and compare them with actual vocal interaction data. Our findings support active sampling as the best model for real-time marmoset monkey vocal exchanges. In some cases, the active sampling model was even able to partially predict the distribution of vocal durations for individuals to approximate the optimal call duration. These results suggest a non-traditional function for primate vocal interactions in which they are used by animals to seek information about their social environments.