Chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) chase prey around obstacles in virtual environments.

Apes require high volumes of energy-rich foods that tend to be patchily distributed, creating evolutionary pressures for flexible and complex cognition. Several species hunt mobile prey, placing demands on working memory and selecting for sociocognitive abilities such as predicting prey behavior. The mechanisms by which apes overcome foraging and hunting challenges are difficult to elucidate. Field investigations provide rich data sets but lack experimental control, limiting the gamut of questions they can answer, while experiments with captive subjects offer lower generalizability to real-world situations. Virtual environments (VEs) present a compromise, combining experimental specificity with proxies of realistic situations. In this study, chimpanzees and bonobos moved through a three-dimensional VE using a touchscreen. All subjects learned to chase and catch moving rabbits, some exhibiting high success rates even in the presence of large obstacles. Success in trials with a first-person (FP) viewpoint was much higher than in trials presented from overhead, suggesting that the immersive nature of FP trials helped subjects to understand their location in the environment better than when they took a top-down view. Data were analyzed using generative computational agent models, identifying that subjects occasionally employed anticipatory hunting strategies, but more often used a direct chasing strategy. This study validates the use of VEs as an experimental paradigm, demonstrating that apes can understand the behavior of moving agents in situations of varying complexity and that computational modeling can be utilized to delve into behavioral data at a fine-grained level and identify which of several cognitive strategies they fit best. (PsycInfo Database Record (c) 2025 APA, all rights reserved).