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bioRxivAnimal Behavior & CognitionPreprint

Virtual Environments for Research into Social Evolution (VERSE): A novel experimental environment for the study of human social learning

C. Easter

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Abstract

1.Social learning (learning from others) can be a cost-effective way of gaining information compared to asocial (independent) learning. However, learning from others indiscriminately can lead to the acquisition of maladaptive behaviours or outdated information. Evolutionary theory therefore predicts that individuals will use social information adaptively through the use of social learning strategies. Restrictive laboratory conditions, however, make studying human learning strategies problematic. Abstract tasks, unrealistic sources of social information and methodologies that do not take into account the influence of physical location over large spaces make it difficult to ascertain if previous findings are representative of the way we would use social information in reality. Here I describe a novel platform for studying human social behaviour within immersive virtual environments: "Virtual Environments for Research into Social Evolution" (VERSE). Through the use of gaming technology, VERSE allows researchers to build realistic, three-dimensional, open world environments where participants can complete ecologically relevant tasks while actively observing computer-controlled artificial intelligence agents (AIs) that act as realistic yet controllable sources of social information. This methodological article begins by exploring what social learning strategies are and the problems with studying social learning behaviour in humans (compared to animal populations, for example). I then discuss how gaming technology can be used in behavioural research and follow on with a detailed account of the specific functionalities available in VERSE. I conclude with a worked example of how VERSE can be used to construct a novel behavioural experiment. Altogether, VERSE has great potential to give us insight into how human individuals learn within novel environments in a way that has never before been possible.

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C. Easter, C. Hassall·bioRxiv·Aug 26, 2022