Humans have an immense behavioural and cognitive repertoire that has been shaped by cumulative cultural evolution. In this thesis I investigate two cognitive abilities that crucially enlarge the efficiency of skill and knowledge acquisition: 1) the capability for abstraction that enables powerful generalization of information to make wide ranging predictions in new situations and 2) the ability to imitate others which allows the quick and low-risk adoption of new behavioural strategies. Despite decades of accumulating data in both domains, it is still debated to what extent other species share these abilities and how they develop in humans. Solving these persisting disagreements requires an alteration of how data are generated and analysed. The use of computational modelling is a promising way to specify hypotheses, perform more detailed analyses of the underlying cognitive mechanisms and thus ultimately achieve a richer species comparison. In this thesis, I introduce the approach of hierarchical Bayesian modelling to the field of comparative psychology to investigate abstract rule formation and action copying in capuchin monkeys, chimpanzees (only abstract rule formation) and children. In chapters two and three, I outline two studies in which participants had to use sampled evidence to infer abstract rules about the item distributions in containers and efficiently guide behaviour in novel test situations. In chapter four, we investigated how children and capuchin monkeys integrate causal and social information when copying a goal- directed behaviour. Whereas children’s performance was mostly in line with the predictions of the computational models, showing that they are capable of abstraction and consider causal information when imitating, capuchin monkeys performed in all experiments at chance and chimpanzees showed some understanding of abstract rules. In chapter five, I discuss how the modelling approach improved my research and outline the advantages and caveats of its application in future comparative and developmental research.
| Date of Award | 1 Dec 2020 |
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| Original language | English |
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| Awarding Institution | |
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| Supervisor | Amanda Seed (Supervisor) |
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Exploring the evolution and ontogeny of imitation and abstraction: a hierarchical Bayesian modelling approach
Felsche, E. (Author). 1 Dec 2020
Student thesis: Doctoral Thesis (PhD)