Abstract
In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees (Pan troglodytes) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition.
Highlights
Roboticists face difficult problems when developing artificial memory systems
Using our closest living phylogenetic relative—the chimpanzee (Pan troglodytes)—as a case study, we offer a methodological primer of how biologists can use the rational analysis approach to study how statistical patterns in the environment can shape cognitive and behavioural systems across species
With the environmental patterns in hand, we modelled chimpanzee memory performance to compare it to the structure of their social environment
Summary
Roboticists face difficult problems when developing artificial memory systems. For one, those systems inevitably come with limited capacity—there are physical bounds to how much information can be stored. In coping with biological (e.g. storage, computational) constraints, human memory must encode, maintain, prioritize and recall information that is relevant to current or future stimuli in the environment, while removing irrelevant records. How can such systems be best designed? One possibility is that the cognitive system could take advantage of statistical regularities in the environment—a thesis that, in cognitive science, has been prominently advanced by Anderson’s [1] rational analysis This framework proposes that cognition is an adaptive response to recurrent environmental structures and provides a step-by-step approach to investigate how cognition solves those information-processing problems. We end by discussing implications of our findings for the evolution of cooperation, cultural transmission, disease transmission and cognitive evolution more generally
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