Task allocation is a central challenge of collective behavior in a variety of group-living species, and this is particularly the case for the allocation of social insect workers for group defense. In social insects, both benefits and considerable costs are associated with the production of specialized soldiers. We asked whether colonies mitigate costs of production of specialized soldiers by simultaneously employing behavioral flexibility in nonspecialist workers that can augment defense capabilities at short time scales. We studied colonies of the stingless bee Tetragonisca angustula, a species that has 2 discrete nest-guarding tasks typically performed by majors: hovering guarding and standing guarding. Majors showed age polyethism across nest-guarding tasks, first hovering and then changing to the task of standing guarding after 1 week. Colonies were also able to reassign minors to guarding tasks when majors were experimentally removed. Replacement guards persisted in nest defense tasks until colonies produced enough majors to return to their initial state. Tetragonisca angustula colonies thus employed a coordinated set of specialization strategies in nest defense: morphologically specialized soldiers, age polyethism among soldiers within specific guarding tasks, and rapid flexible reallocation of nonspecialists to guarding during soldier loss. This mixed strategy achieves the benefits of a highly specialized defensive force while maintaining the potential for rapid reinforcement when soldiers are lost or colonies face unexpectedly intense attack.

Behavioral correlations stretching over time are an essential but often neglected aspect of interactions among animals. These correlations pose a challenge to current behavioral-analysis methods that lack effective means to analyze complex series of interactions. Here we show that non-invasive information-theoretic tools can be used to reveal communication protocols that guide complex social interactions by measuring simultaneous flows of different types of information between subjects. We demonstrate this approach by showing that the tandem-running behavior of the ant Temnothorax rugatulus and that of the termites Coptotermes formosanus and Reticulitermes speratus are governed by different communication protocols. Our discovery reconciles the diverse ultimate causes of tandem running across these two taxa with their apparently similar signaling mechanisms. We show that bidirectional flow of information is present only in ants and is consistent with the use of acknowledgement signals to regulate the flow of directional information.

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In many sports, athletes perform motor tasks that simultaneously require both speed and accuracy for success, such as kicking a ball. Because of the biomechanical trade-off between speed and accuracy, athletes must balance these competing demands. Modelling the optimal compromise between speed and accuracy requires one to quantifyhow task speed affects the dispersion around a target, a level of experimental detail not previously addressed. Using soccer penalties as a system, we measured two-dimensional kicking error over a range of speeds, target heights, and kicking techniques. Twenty experienced soccer players executed a total of 8466 kicks at two targets (high and low). Players kicked with the side of their foot or the instep at ball speeds ranging from 40% to 100% of their maximum. The inaccuracy of kicks was measured in horizontal and vertical dimensions. For both horizontal and vertical inaccuracy, variance increased as a power function of speed, whose parameter values depended on the combination of kicking technique and target height. Kicking precision was greater when aiming at a low target compared to a high target. Side-foot kicks were more accurate than instep kicks. The centre of the dispersion of shots shifted as a function of speed. An analysis of the covariance between horizontal and vertical error revealed right-footed kickers tended to miss below and to the left of the target or above and to the right, while left-footed kickers tended along the reflected axis. Our analysis provides relationships needed to model the optimal strategy for penalty kickers.

As being killed and eaten results in zero future fitness, habitats with high predation risk can exert strong selective pressure on the evolution of animal behaviour (Laundré et al., 2010). Many studies have examined how habitat features affect predation risk, typically focussing on how the amount of available cover affects the probability of being detected by predators (Dickman, 1992; Iribarren

In this paper, we present an approach to designing decentralized robot control policies that mimic certain microscopic and macroscopic behaviors of ants performing collective transport tasks. In prior work, we used a stochastic hybrid system model to characterize the observed team dynamics of ant group retrieval of a rigid load. We have also used macroscopic population dynamic models to design enzyme-inspired stochastic control policies that allocate a robotic swarm around multiple boundaries in a way that is robust to environmental variations. Here, we build on this prior work to synthesize stochastic robot attachment-detachment policies for tasks in which a robotic swarm must achieve non-uniform spatial distributions around multiple loads and transport them at a constant velocity. Three methods are presented for designing robot control policies that replicate the steady-state distributions, transient dynamics, and fluxes between states that we have observed in ant populations during group retrieval. The equilibrium population matching method (EPMM) can be used to achieve a desired transport team composition as quickly as possible; the transient matching method (TMM) can control the transient population dynamics of the team while driving it to the desired composition; and the rate matching method (RMM) regulates the rates at which robots join and leave a load during transport. We validate our model predictions in an agent-based simulation, verify that each controller design method produces successful transport of a load at a regulated velocity, and compare the advantages and disadvantages of each method.

Although optimal foraging theory predicts that natural selection should favor animal behaviors that maximize long-term rate of gain, behaviors observed in the laboratory tend to be impulsive. In binary-choice experiments, despite the long-term gain of each alternative, animals favor short handling times. Most explanations of this behavior suggest that there is hidden rationality in impulsiveness. Instead, we suggest that simultaneous and mutually exclusive binary-choice encounters are often unnatural and thus immune to the effects of natural selection. Using a simulation of an imperfect forager, we show how a simple strategy (i.e., an intuitive model of animal behavior) that maximizes long-term rate of gain under natural conditions appears to be impulsive under operant laboratory conditions. We then show how the accuracy of this model can be verified in the laboratory by biasing subjects with a short pre-experiment ad libitum high-quality feeding period. We also show a similar behavioral mechanism results in diet preferences that are qualitatively consistent with the digestive rate model of foraging (i.e., foraging under digestive rate constraints).

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