How can we apply decision-making theories to wild animal behavior? Predictions arising from dual process theory and Bayesian decision theory

Abstract

Our understanding of decision-making processes and cognitive biases is ever increasing, thanks to an accumulation of testable models and a large body of research over the last several decades. The vast majority of this work has been done in humans and laboratory animals because these study subjects and situations allow for tightly controlled experiments. However, it raises questions about how this knowledge can be applied to wild animals in their complex environments. Here, we review two prominent decision-making theories, dual process theory and Bayesian decision theory, to assess the similarities in these approaches and consider how they may apply to wild animals living in heterogenous environments within complicated social groupings. In particular, we wanted to assess when wild animals are likely to respond to a situation with a quick heuristic decision and when they are likely to spend more time and energy on the decision-making process. Based on the literature and evidence from our multi-destination routing experiments on primates, we find that individuals are likely to make quick, heuristic decisions when they encounter routine situations, or signals/cues that accurately predict a certain outcome, or easy problems that experience or evolutionary history has prepared them for. Conversely, effortful decision-making is likely in novel or surprising situations, when signals and cues have unpredictable or uncertain relationships to an outcome, and when problems are computationally complex. Though if problems are overly complex, satisficing via heuristics is likely, to avoid costly mental effort. We present hypotheses for how animals with different socio-ecologies may have to distribute their cognitive effort. Finally, we examine the conservation implications and potential cognitive overload for animals experiencing increasingly novel situations caused by current human-induced rapid environmental change.

Keywords: anthropocene; cognitive overload; heuristics; mental effort; satisficing.

Figure 1

Schematic of Bayesian decision making (Modified from Ma, 2019).

Figure 2

Performance of three individual wild vervet monkeys (Chlorocebus pygerythrus) completing a pentagon shaped foraging array with five food platforms baited identically (Kumpan et al., 2019) versus the performance of three other individuals completing a Z‐shaped array with six platforms baited identically (data only shown when beginning at the corner of the Z on platform 5, Teichroeb & Smeltzer, 2018) at Nabugabo, Uganda. The similarity index shows the similarity of the path taken on each trial over time relative to the path the individual took on the previous trial (Saleh & Chittka, 2007). Error bars show standard error. In the pentagon array, individuals immediately used the path that goes around the outside of the pentagon, which corresponded to the shortest path, and rarely deviated from it. For the Z‐array, the monkeys sampled different paths before settling into a more consistent way to solve the array.

Figure 3

Graphs depicting the theoretical amount of mental effort an animal should exert depending on how routine a situation is, how accurately a cue or signal predicts an outcome, or how computationally complex a problem is.