In computer science

Computer science

Computer science or computing science is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems...

, Artificial Ants stand for multi-agent methods inspired by the behavior of real ants. The pheromone-based communication of biological ant

Ant

Ants are social insects of the family Formicidae and, along with the related wasps and bees, belong to the order Hymenoptera. Ants evolved from wasp-like ancestors in the mid-Cretaceous period between 110 and 130 million years ago and diversified after the rise of flowering plants. More than...

s is often the predominant paradigm used. Combinations of Artificial Ants and local search

Local search (optimization)

In computer science, local search is a metaheuristic method for solving computationally hard optimization problems. Local search can be used on problems that can be formulated as finding a solution maximizing a criterion among a number of candidate solutions...

 algorithms have become a method of choice for numerous optimization tasks involving some sort of graph

Graph (mathematics)

In mathematics, a graph is an abstract representation of a set of objects where some pairs of the objects are connected by links. The interconnected objects are represented by mathematical abstractions called vertices, and the links that connect some pairs of vertices are called edges...

, e. g., vehicle routing

Vehicle routing problem

The vehicle routing problem is a combinatorial optimization and integer programming problem seeking to service a number of customers with a fleet of vehicles. Proposed by Dantzig and Ramser in 1959, VRP is an important problem in the fields of transportation, distribution and logistics...

 and internet routing

Routing

Routing is the process of selecting paths in a network along which to send network traffic. Routing is performed for many kinds of networks, including the telephone network , electronic data networks , and transportation networks...

. The burgeoning activity in this field has led to conferences dedicated solely to Artificial Ants, and to numerous commercial applications by specialized companies such as AntOptima

AntOptima

AntOptima is a company that split off from the Swiss artificial intelligence laboratory IDSIA, dedicated to the commercial exploitation of optimization algorithms based on Artificial Ants and Ant Colony Optimization...

. As an example, Ant colony optimization

Ant colony optimization

In computer science and operations research, the ant colony optimization algorithm ' is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs....

  is a class of optimization

Optimization (computer science)

In computer science, program optimization or software optimization is the process of modifying a software system to make some aspect of it work more efficiently or use fewer resources...

 algorithm

Algorithm

In mathematics and computer science, an algorithm is an effective method expressed as a finite list of well-defined instructions for calculating a function. Algorithms are used for calculation, data processing, and automated reasoning...

s modeled on the actions of an ant colony

Ant colony

An ant colony is an underground lair where ants live, eat and mate. Colonies consist of a series of underground chambers, connected to each other and the surface of the earth by small tunnels. There are rooms for nurseries, food storage, and mating...

. Artificial 'ants' (e.g. simulation agents) locate optimal solutions by moving through a parameter space

Parameter space

In science, a parameter space is the set of values of parameters encountered in a particular mathematical model. Often the parameters are inputs of a function, in which case the technical term for the parameter space is domain of a function....

 representing all possible solutions. Real ants lay down pheromone

Pheromone

A pheromone is a secreted or excreted chemical factor that triggers a social response in members of the same species. Pheromones are chemicals capable of acting outside the body of the secreting individual to impact the behavior of the receiving individual...

s directing each other to resources while exploring their environment. The simulated 'ants' similarly record their positions and the quality of their solutions, so that in later simulation iterations more ants locate better solutions. One variation on this approach is the bees algorithm

Bees algorithm

In computer science and operations research, the bees algorithm is a population-based search algorithm first developed in 2005. It mimics the food foraging behaviour of swarms of honey bees...

, which is more analogous to the foraging patterns of the honey bee

Honey bee

Honey bees are a subset of bees in the genus Apis, primarily distinguished by the production and storage of honey and the construction of perennial, colonial nests out of wax. Honey bees are the only extant members of the tribe Apini, all in the genus Apis...

, another social insect.

The inventors are Frans Moyson and Bernard Manderick. Pioneers of the field include Marco Dorigo

Marco Dorigo

Marco Dorigo is a research director for the Belgian Funds for Scientific Research , a professor in the computer science department of the University of Paderborn and a co-director of , the artificial intelligence lab of the Université Libre de Bruxelles.He is the proponent of the "ant colony...

, Luca Maria Gambardella

Luca Maria Gambardella

Luca Maria Gambardella has been co-director of the Swiss AI lab IDSIA since 1995. Together with former IDSIA senior researcher Marco Dorigo and others he made substantial contributions to the rapidly growing research field of ant colony optimization, a set of multi-agent methods inspired by the...

.

For more details, see the page of the paradigm Ant Colony Optimization

Ambient networks of intelligent objects

New concepts are required since “intelligence” is no longer centralized but can be found throughout all minuscule objects. Anthropocentric concepts have always led us to the production of IT systems in which data processing, control units and calculating forces are centralized. These centralized units have continually increased their performance and can be compared to the human brain. The model of the brain has become the ultimate vision of computers. Ambient networks of intelligent objects and, sooner or later, a new generation of information systems which are even more diffused and based on nanotechnology, will profoundly change this concept. Small devices that can be compared to insects do not dispose of a high intelligence on their own. Indeed, their intelligence can be classed as fairly limited. It is, for example, impossible to integrate a high performance calculator with the power to solve any kind of mathematical problem into a biochip that is implanted into the human body or integrated in an intelligent tag which is designed to trace commercial articles. However, once those objects are interconnected they dispose of a form of intelligence that can be compared to a colony of ants or bees. In the case of certain problems, this type of intelligence can be superior to the reasoning of a centralized system similar to the brain.

Nature has given us several examples of how minuscule organisms, if they all follow the same basic rule, can create a form of collective intelligence

Collective intelligence

Collective intelligence is a shared or group intelligence that emerges from the collaboration and competition of many individuals and appears in consensus decision making in bacteria, animals, humans and computer networks....

on the macroscopic level. Colonies of social insects perfectly illustrate this model which greatly differs from human societies. This model is based on the co-operation of independent units with simple and unpredictable behavior. They move through their surrounding area to carry out certain tasks and only possess a very limited amount of information to do so. A colony of ants, for example, represents numerous qualities that can also be applied to a network of ambient objects. Colonies of ants have a very high capacity to adapt themselves to changes in the environment as well as an enormous strength in dealing with situations where one individual fails to carry out a given task. This kind of flexibility would also be very useful for mobile networks of objects which are perpetually developing. Parcels of information that move from a computer to a digital object behave in the same way as ants would do. They move through the network and pass from one knot to the next with the objective of arriving at their final destination as quickly as possible.