Biologically inspired ant colony simulation

We present a unified biologically inspired approach to simulate ant colonies inspired by the key observation of collective behaviors of ants in nature. To generate the trajectories of virtual ants, we construct a motion controller to determine the motion states and the paths of virtual ants, considering dynamic internal and external interactions. The motion controller computes a target position for each ant at every time step according to its motion states. The motion states include four states: basic movement, the stop state, and two dynamic interactions (i.e., internal and external, respectively referring to interaction with neighbors for necessary information transfer about the destination, and interaction with surroundings such as food sources, nests, and obstacles) to represent basic exploration, casual or intentional stop, and purposeful movement, respectively. Based on the motion states, the motion controller plans an optimal path for each virtual ant. Through many simulation experiments, we demonstrate that our method is controllable, scalable, and flexible to simulate hybrid colonies with a large number of ants.