AntAnts are eusocial insects of the family Formicidae and, along with the related wasps and bees, belong to the order Hymenoptera. Ants evolved from vespoid wasp ancestors in the Cretaceous period. More than 13,800 of an estimated total of 22,000 species have been classified. They are easily identified by their geniculate (elbowed) antennae and the distinctive node-like structure that forms their slender waists.
Myrmecia (ant)Myrmecia is a genus of ants first established by Danish zoologist Johan Christian Fabricius in 1804. The genus is a member of the subfamily Myrmeciinae of the family Formicidae. Myrmecia is a large genus of ants, comprising at least 93 species that are found throughout Australia and its coastal islands, while a single species is only known from New Caledonia. One species has been introduced out of its natural distribution and was found in New Zealand in 1940, but the ant was last seen in 1981.
Ant colony optimization algorithmsIn computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial ants stand for multi-agent methods inspired by the behavior of real ants. The pheromone-based communication of biological ants is often the predominant paradigm used. Combinations of artificial ants and local search algorithms have become a method of choice for numerous optimization tasks involving some sort of graph, e.
Leafcutter antLeafcutter ants, a non-generic name, are any of 47 species of leaf-chewing ants belonging to the two genera Atta and Acromyrmex. These species of tropical, fungus-growing ants are all endemic to South and Central America, Mexico, and parts of the southern United States. Leafcutter ants can carry twenty times their body weight and cut and process fresh vegetation (leaves, flowers, and grasses) to serve as the nutritional substrate for their fungal cultivates.
Computational complexityIn computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements. The complexity of a problem is the complexity of the best algorithms that allow solving the problem. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.
Computational complexity theoryIn theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used.
Argentine antThe Argentine ant (Linepithema humile, formerly Iridomyrmex humilis) is an ant native to northern Argentina, Uruguay, Paraguay, Bolivia and southern Brazil. This invasive species was inadvertently introduced by humans on a global scale and has become established in many Mediterranean climate areas, including South Africa, New Zealand, Japan, Easter Island, Australia, Europe, Hawaii, and the continental United States.
Global optimizationGlobal optimization is a branch of applied mathematics and numerical analysis that attempts to find the global minima or maxima of a function or a set of functions on a given set. It is usually described as a minimization problem because the maximization of the real-valued function is equivalent to the minimization of the function . Given a possibly nonlinear and non-convex continuous function with the global minima and the set of all global minimizers in , the standard minimization problem can be given as that is, finding and a global minimizer in ; where is a (not necessarily convex) compact set defined by inequalities .
Particle swarm optimizationIn computational science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formula over the particle's position and velocity.
Swarm behaviourSwarm behaviour, or swarming, is a collective behaviour exhibited by entities, particularly animals, of similar size which aggregate together, perhaps milling about the same spot or perhaps moving en masse or migrating in some direction. It is a highly interdisciplinary topic. As a term, swarming is applied particularly to insects, but can also be applied to any other entity or animal that exhibits swarm behaviour.
