Long-tailed macaques extract statistical information from repeated types of events to make rational decisions under uncertainty

Abstract

Human children and apes seem to be intuitive statisticians when making predictions from populations of objects to randomly drawn samples, whereas monkeys seem not to be. Statistical reasoning can also be investigated in tasks in which the probabilities of different possibilities must be inferred from relative frequencies of events, but little is known about the performance of nonhuman primates in such tasks. In the current study, we investigated whether long-tailed macaques extract statistical information from repeated types of events to make predictions under uncertainty. In each experiment, monkeys first experienced the probability of rewards associated with different factors separately. In a subsequent test trial, monkeys could then choose between the different factors presented simultaneously. In Experiment 1, we tested whether long-tailed macaques relied on probabilities and not on a comparison of absolute quantities to make predictions. In Experiment 2 and 3 we varied the nature of the predictive factors and the complexity of the covariation structure between rewards and factors. Results indicate that long-tailed macaques extract statistical information from repeated types of events to make predictions and rational decisions under uncertainty, in more or less complex scenarios. These findings suggest that the presentation format affects the monkeys’ statistical reasoning abilities.

How does social context modulate risky decision-making in long-tailed macaques (Macaca fascicularis)? A research report on problematic issues with a repeated sampling from experience paradigm

“…The most important lesson we learned from this project was that we had tremendously underestimated how much sampling experience was necessary for the subjects to make optimal choices as a function of risk box color. This is particularly surprising considering that individuals from this group of long-tailed macaques were previously found to be competent in extracting statistical information from repeated events to make optimal decisions in subsequent test trials (Placì et al, 2019). In Experiment 1 of the Plací et al study, the monkeys obtained information about two tokens (a blue and an orange metal carabiner).…”

Macphail’s Null Hypothesis of Vertebrate Intelligence: Insights From Avian Cognition

“…On the other hand, both the great apes and the New Zealand mountain parrot, the kea, make their choices by relying on probabilistic information, by comparing the ratios of objects within and between the two populations (Rakoczy et al, 2014;Bastos and Taylor, 2020). This ability, known as true statistical inference, has so far not been conclusively shown outside of these two taxa, as other studies on primates and birds have not been able to exclude the absolute number heuristic as a potential strategy (Clements et al, 2018;Roberts et al, 2018;De Petrillo and Rosati, 2019;Placì et al, 2019).…”

Giraffes make decisions based on statistical information

“…predicting the probability of rewards based on the relative frequencies of objects 11 ) can only be reliably demonstrated after ruling out alternative explanations based on simpler quantity heuristics (e.g. "select the container with a higher number of highly-liked food", or "avoid the container with a higher number of less-preferred food" 12 ).Great apes, long-tailed macaques (Macaca fascicularis) and keas (Nestor notabilis) have shown statistical reasoning, using relative frequencies of items to predict sampling events 11,[13][14][15][16] . Moreover, keas could combine information across different domains, integrating physical and social information when making statistical decisions 11 , in contrast to chimpanzees that succeeded in integrating social information, but failed to integrate physical information when predicting sampling outcomes 17 .…”

“…Great apes, long-tailed macaques (Macaca fascicularis) and keas (Nestor notabilis) have shown statistical reasoning, using relative frequencies of items to predict sampling events 11,[13][14][15][16] . Moreover, keas could combine information across different domains, integrating physical and social information when making statistical decisions 11 , in contrast to chimpanzees that succeeded in integrating social information, but failed to integrate physical information when predicting sampling outcomes 17 .…”