Sampling and decision rules used by honey bees in a foraging arena

Animals must continuously choose among various available options to exploit the most profitable resource. They also need to keep themselves updated about the values of all available options, since their relative values can change quickly due to depletion or exploitation by competitors. While the sampling and decision rules by which foragers profitably exploit a flower patch have attracted a great deal of attention in theory and experiments with bumble bees, similar rules for honey bee foragers, which face similar foraging challenges, are not as well studied. By presenting foragers of the honey bee Apis cerana with choice tests in a foraging arena and recording their behavior, we investigate possible sampling and decision rules that the foragers use to choose one option over another and to track other options. We show that a large part of the sampling and decision-making process of a foraging honey bee can be explained by decomposing the choice behavior into dichotomous decision points and incorporating the cost of sampling. The results suggest that a honey bee forager, by using a few simple rules as part of a Bayesian inference process, is able to effectively deal with the complex task of successfully exploiting foraging patches that consist of dynamic and multiple options.