Lixiang Li
Beijing University of Posts and Telecommunications, China
Title: Foraging behavior of ants and its application in optimization field
Biography
Biography: Lixiang Li
Abstract
Ants and other social animals have captured the attention of many scientists because of their self-organizing behavior and the high level of structuration their colonies can achieve, especially when compared to the relative simplicity of the individuals. The study of the foraging behavior of group animals (especially ants) is of practical ecological importance, but it also contributes to the development of widely applicable optimization problem-solving techniques. In recent years, algorithms inspired by models of animal group behaviors have achieved increasing success among researchers in computer science, communication networks and operations research. This talk introduces basic mechanisms of effective foraging for social insects or group animals that have a home. The whole foraging process of ants is controlled by three successive strategies: hunting, homing, and path building. These learning strategies have advantages on the internet optimization process. This speech also introduces some dynamical models of ant foraging. We introduce the influences of the special region around the nest, the size of the food source, the search range, the limitation of ants’ physical ability, and ants’ learning process with respect to foraging behavior. Our analysis suggests that group animals that have a home do not perform random walks, but rather deterministic walks in a random environment. They use their knowledge to guide them and their behavior is also influenced by their physical abilities, their age, and the existence of homes. In this talk, we will also introduce the application fields of ant foraging behavior, such as network optimization, signal processing, network security, distributed control et al.