Emergent algorithm
Encyclopedia
An emergent algorithm is an algorithm
that has the following characteristics:
Emergence is said to arise from the cooperation of many simple processes, i.e. high-level behaviour resulting from low-level interaction of simpler building blocks. One example of emergent behaviour that has been studied over recent years is that of 'flocking'. In a 'flock of birds', the flock is a dynamic entity consisting of hundreds (or thousands) of individuals. The flock constantly changes shape and direction but maintains overall cohesion. Using cellular automata and treating each bird in the flock as an autonomous agent, with simple local rules controlling agent behaviour relative to closest neighbouring birds, a system can be constructed where the overall behaviour of the collective agents reflects the behaviour of the real flock.
Examples of emergent algorithms and models include cellular automata, artificial neural networks and swarm intelligence
systems (ant colony optimization
, bees algorithm
, etc.).
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...
that has the following characteristics:
- it achieves predictable global effects
- it does not require global visibility
- it does not assume any kind of centralized control
- it is self-stabilizing
Emergence is said to arise from the cooperation of many simple processes, i.e. high-level behaviour resulting from low-level interaction of simpler building blocks. One example of emergent behaviour that has been studied over recent years is that of 'flocking'. In a 'flock of birds', the flock is a dynamic entity consisting of hundreds (or thousands) of individuals. The flock constantly changes shape and direction but maintains overall cohesion. Using cellular automata and treating each bird in the flock as an autonomous agent, with simple local rules controlling agent behaviour relative to closest neighbouring birds, a system can be constructed where the overall behaviour of the collective agents reflects the behaviour of the real flock.
Examples of emergent algorithms and models include cellular automata, artificial neural networks and swarm intelligence
Swarm intelligence
Swarm intelligence is the collective behaviour of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence...
systems (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....
, 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...
, etc.).
See also
- EmergenceEmergenceIn philosophy, systems theory, science, and art, emergence is the way complex systems and patterns arise out of a multiplicity of relatively simple interactions. Emergence is central to the theories of integrative levels and of complex systems....
- Evolutionary computationEvolutionary computationIn computer science, evolutionary computation is a subfield of artificial intelligence that involves combinatorial optimization problems....
- Genetic algorithmGenetic algorithmA genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems...
- HeuristicHeuristicHeuristic refers to experience-based techniques for problem solving, learning, and discovery. Heuristic methods are used to speed up the process of finding a satisfactory solution, where an exhaustive search is impractical...