Individual and collective foraging in autonomous search agents with human intervention

Humans and other complex organisms exhibit intelligent behaviors as individual agents and as groups of coordinated agents. They can switch between independent and collective modes of behavior, and flexible switching can be advantageous for adapting to ongoing changes in conditions. In the present study, we investigated the flexibility between independent and collective modes of behavior in a simulated social foraging task designed to benefit from both modes: distancing among ten foraging agents promoted faster detection of resources, whereas flocking promoted faster consumption. There was a tradeoff between faster detection versus faster consumption, but both factors contributed to foraging success. Results showed that group foraging performance among simulated agents was enhanced by loose coupling that balanced distancing and flocking among agents and enabled them to fluidly switch among a variety of groupings. We also examined the effects of more sophisticated cognitive capacities by studying how human players improve performance when they control one of the search agents. Results showed that human intervention further enhanced group performance with loosely coupled agents, and human foragers performed better when coordinating with loosely coupled agents. Humans players adapted their balance of independent versus collective search modes in response to the dynamics of simulated agents, thereby demonstrating the importance of adaptive flexibility in social foraging.

Role of the pheromone for orientation in the group foraging ant, Veromessor pergandei

Role of the pheromone for orientation in the group foraging ant, Veromessor pergandei Navigation is comprised of a variety of strategies which rely on multiple external cues to shape a navigator’s behavioral output. An additional navigational challenge is coping with forces such as wind and water currents that push navigators off-course. Here, we explore the cue interactions that dictate orientation and foragers’ ability to counter course altering rotational changes in the desert ant, Veromessor pergandei. We found a cross sensory interaction between the pheromone cue and the path integrator underlies correct orientation during the inbound journey. The celestial compass provides directional information while the presence of the trail pheromone acts as a critical context cue, triggering distinct behavioral responses (vector orientation, search and backtracking). A particularly interesting interaction occurs between the pheromone and the forager’s vector state. While exposed to the pheromone, foragers orient to the vector direction regardless of vector state, while in the pheromone’s absence the current vector triggers the switch between behaviors. Such interactions maximize the foragers’ return to the nest and inhibit movement off the trail. Finally, our manipulations continuously pushed foragers away from their desired heading, yet foragers were highly proficient at counteracting these changes, steering to maintain a correct heading even at rotational speeds of ~40°/s.

Neural encoding of socially adjusted value during competitive and hazardous foraging

In group foraging organisms, optimizing the conflicting demands of competitive food loss and safety is critical. We demonstrate that humans select competition avoidant and risk diluting strategies during foraging depending on socially adjusted value. We formulate a mathematically grounded quantification of socially adjusted value in foraging environments and show using multivariate fMRI analyses that socially adjusted value is encoded by mid-cingulate and ventromedial prefrontal cortices, regions that integrate value and action signals.

Social interactions drive efficient foraging and income equality in groups of fish

The social interactions underlying group foraging and their benefits have been mostly studied using mechanistic models replicating qualitative features of group behavior, and focused on a single resource or a few clustered ones. Here, we tracked groups of freely foraging adult zebrafish with spatially dispersed food items and found that fish perform stereotypical maneuvers when consuming food, which attract neighboring fish. We then present a mathematical model, based on inferred functional interactions between fish, which accurately describes individual and group foraging of real fish. We show that these interactions allow fish to combine individual and social information to achieve near-optimal foraging efficiency and promote income equality within groups. We further show that the interactions that would maximize efficiency in these social foraging models depend on group size, but not on food distribution, and hypothesize that fish may adaptively pick the subgroup of neighbors they ‘listen to’ to determine their own behavior.

Effects of the cleaner fish Labroides dimidiatus on grazing fishes and coral reef benthos

Territorial and roving grazing fishes farm, and feed on, algae, sediment, or detritus, thus exerting different influences on benthic community structure, and are common clients of cleaner fish. Whether cleaners affect grazing-fish diversity and abundance, and indirectly the benthos, was tested using reefs maintained free of the bluestreak cleaner wrasse Labroides dimidiatus for 8.5 yr (removals) compared with controls. We quantified fish abundance per grazing functional group, foraging rates of roving grazers, cleaning rates of roving grazers by L. dimidiatus, reef benthos composition, and fouling material on settlement tiles. Abundances of ‘intensive’ and ‘extensive’ territorial farmers, non-farmers, parrotfishes and Acanthurus spp. were lower on removal than control reefs, but this was not the case for ‘indeterminate’ farmers and Ctenochaetus striatus. Foraging rates of Acanthurus spp. and C. striatus were unaffected by cleaner presence or cleaning duration. This suggests some robustness of the grazers’ foraging behaviour to loss of cleaners. Acanthurus spp. foraged predominantly on sediment and detritus, whereas C. striatus and parrotfishes grazed over algal turfs. Nevertheless, benthic community structure and amount of organic and inorganic material that accumulated over 3.5 mo on tiles were not affected by cleaner presence. Thus, despite greater abundances of many roving grazers, and consequently higher grazing rates being linked to the presence of cleaners, the benthos was not detectably affected by cleaners. This reveals that the positive effect of cleaners on fish abundance is not associated with a subsequent change in the benthos as predicted. Rather, it suggests a resilience of benthic community structure to cleaner-fish loss, possibly related to multiple antagonistic effects of different grazer functional groups. However, losing cleaners remains a problem for reefs, as the lack of cleaning has adverse consequences for fish physiology and populations.

Cooperative foraging during larval stage affects fitness in Drosophila

SummaryCooperative behavior can confer advantages to animals. This is especially true for cooperative foraging which provides fitness benefits through more efficient acquisition and consumption of food. While examples of group foraging have been widely described, the principles governing formation of such aggregations and rules that determine group membership remain poorly understood. Here we take advantage of an experimental model system featuring cooperative foraging behavior in Drosophila. Under crowded conditions, fly larvae form coordinated digging groups (clusters), where individuals are linked together by sensory cues and group membership requires prior experience. However, fitness benefits of Drosophila larval clustering remain unknown. We demonstrate that animals raised in crowded conditions on food partially processed by other larvae experience a developmental delay presumably due to the decreased nutritional value of the substrate. Intriguingly, same conditions promote formation of cooperative foraging clusters which further extends larval stage compared to non-clustering animals. Remarkably, this developmental retardation also results in a relative increase in wing size, serving an indicator of adult fitness. Thus, we find that the clustering-induced developmental delay is accompanied by fitness benefits. Therefore, cooperative foraging, while delaying development, may have evolved to give Drosophila larvae benefits when presented with competition for limited food resources.

Revisiting Parameters of Bioinspired Behavior Models in Group Foraging Modeling

Using bioinspired models and methods is one of approaches for solving tasks of swarm robotics. In this paper one of such tasks, modeling of foraging, and it’s solving by creating analogues of social structures of ants and models of feeding behavior are considered. The most important characteristics of ants’ colonies for modeling were defined – individuals number in society and it’s structure, workers’ speed, a communication distance and working area size. Besides, existing experimental basis (a group of robots and a polygon) was estimated for a usage as a hardware platform for experiments. Several models of feeding behavior were considered: a model without foragers’ functions differentiation and a model with differentiation on active and passive ones. Active foragers look for resources by themselves, then they involve passive foragers; passive foragers are settled on a base, while are not involved in harvesting. A set of finite state machines describe the behavior of agents: basic automatons (provide basic behavior functions) and a meta- automaton, that switches with some conditions an execution of basic automatons. Basic movements were tested on experimental basis. A complex test of models were conducted in a simulation program Kvorum. An analogue of real polygon was made in the program. Modeling consists of series of experiments for every model in which agents must harvest resources. Series differ from each other by number of agents. For models’ quality estimation a ratio of received energy to average obtaining time. Experiments settle that model with functions differentiation works more effective.