5:15 PM - 7:15 PM
[O08-P11] Study on Cooperative Collective Behaviors in Ants
★Invited Papers
Keywords:Ants, Cooperative Behavior, Collective Behavior, Mathematical Model, Automatic Measurement
To survive as a colony, ants allocate various tasks, such as foraging, defense, and cleaning. A key characteristic of ant colonies is that they are not simply groups of individuals; only the queen ant is responsible for reproduction, while the non-reproductive ants are known as workers. This limited reproductive function is referred to as the reproductive division of labor. Workers perform essential activities to maintain the colony's function. Ants in colonies with this reproductive division of labor are recognized as social insects.
Although the term "queen" may suggest a hierarchical society similar to that of humans, the primary role of the queen ant is to lay eggs, and she typically does not give instructions to the workers. Instead, workers autonomously assess the colony's needs and take necessary actions. For example, they care for the eggs and larvae laid by the queen, forage for food, secure water, and maintain a clean nest environment. Workers' autonomous and distributed behavior is driven by their independent judgments, informed by communication among themselves and their observations.
The decentralized behavior of ant colonies serves as a striking example of self-organization. For instance, in small ant species like the brown ant, collective foraging is facilitated through chemical signals known as pheromones. This phenomenon is commonly referred to as "ant marching." When a worker finds food, it returns to the nest, leaving pheromones on the ground at critical points. While searching for food, other workers detect these pheromones and can quickly locate the food by following the trail left by the initial worker. The worker that finds food lays down more pheromones, creating a positive feedback loop that enhances the guidance route connecting the food source to the nest. Consequently, numerous ants can swiftly move from the nest to the food source and transport a significant amount of food back to the colony.
The effectiveness of collective foraging using pheromones relies on workers' ability to sense these chemical signals. However, research by Deneubourg et al. indicates that not all workers can accurately detect pheromones; a certain percentage may deviate from the pheromone path. This study utilized numerical simulations to analyze the impact of these workers on the colony's foraging efficiency. Foraging efficiency, the amount of food transported per unit of time, was evaluated to quantify collective behavior using pheromones.
In the simulations, workers were modeled as agents moving in a two-dimensional triangular lattice space, with the nest as the starting point and two feeding sites. Each worker's stochastic movement on the lattice depended on the pheromone concentration at each point. We introduced two types of ants: normal ants, which detect pheromone concentrations with regular sensitivity, and low-sensitivity ants, which are less responsive to differences in pheromone concentrations. The results indicated that foraging efficiency can improve with the right combination of low-sensitivity and normal-sensitivity ants, depending on the spatial arrangement of food sources and the sensitivity of the low-sensitivity ants.
Furthermore, while it is commonly known that ant colonies often divide labor based on age and experience, this study revealed a different kind of labor division based on sensitivity among workers performing similar tasks. This variation in sensitivity among workers can enhance overall foraging efficiency within the colony.
Although the term "queen" may suggest a hierarchical society similar to that of humans, the primary role of the queen ant is to lay eggs, and she typically does not give instructions to the workers. Instead, workers autonomously assess the colony's needs and take necessary actions. For example, they care for the eggs and larvae laid by the queen, forage for food, secure water, and maintain a clean nest environment. Workers' autonomous and distributed behavior is driven by their independent judgments, informed by communication among themselves and their observations.
The decentralized behavior of ant colonies serves as a striking example of self-organization. For instance, in small ant species like the brown ant, collective foraging is facilitated through chemical signals known as pheromones. This phenomenon is commonly referred to as "ant marching." When a worker finds food, it returns to the nest, leaving pheromones on the ground at critical points. While searching for food, other workers detect these pheromones and can quickly locate the food by following the trail left by the initial worker. The worker that finds food lays down more pheromones, creating a positive feedback loop that enhances the guidance route connecting the food source to the nest. Consequently, numerous ants can swiftly move from the nest to the food source and transport a significant amount of food back to the colony.
The effectiveness of collective foraging using pheromones relies on workers' ability to sense these chemical signals. However, research by Deneubourg et al. indicates that not all workers can accurately detect pheromones; a certain percentage may deviate from the pheromone path. This study utilized numerical simulations to analyze the impact of these workers on the colony's foraging efficiency. Foraging efficiency, the amount of food transported per unit of time, was evaluated to quantify collective behavior using pheromones.
In the simulations, workers were modeled as agents moving in a two-dimensional triangular lattice space, with the nest as the starting point and two feeding sites. Each worker's stochastic movement on the lattice depended on the pheromone concentration at each point. We introduced two types of ants: normal ants, which detect pheromone concentrations with regular sensitivity, and low-sensitivity ants, which are less responsive to differences in pheromone concentrations. The results indicated that foraging efficiency can improve with the right combination of low-sensitivity and normal-sensitivity ants, depending on the spatial arrangement of food sources and the sensitivity of the low-sensitivity ants.
Furthermore, while it is commonly known that ant colonies often divide labor based on age and experience, this study revealed a different kind of labor division based on sensitivity among workers performing similar tasks. This variation in sensitivity among workers can enhance overall foraging efficiency within the colony.