Emergent algorithm
{{short description|Algorithm exhibiting emergent behavior}}
An emergent algorithm is an algorithm that exhibits emergent behavior. In essence an emergent algorithm implements a set of simple building block behaviors that when combined exhibit more complex behaviors. One example of this is the implementation of fuzzy motion controllers used to adapt robot movement in response to environmental obstacles.[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.97.8106&rep=rep1&type=pdf Emergent behaviors of a fuzzy sensory-motor controller evolved by genetic algorithm], Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on (Volume: 31, Issue: 6)
An emergent algorithm has the following characteristics: {{dubious|date=May 2013}}
- it achieves predictable global effects
- it does not require global visibility
- it does not assume any kind of centralized control
- it is self-stabilizing
Other examples of emergent algorithms and models include cellular automata,{{cite conference
| first = Klaus A.
| last = Brunner
| title = What's emergent in Emergent Computing?
| book-title = Cybernetics and Systems 2002: Proceedings of the 16th European Meeting on Cybernetics and Systems Research
| place = Vienna
| pages = 189–192
| volume = 1
| url = http://klaus.e175.net/emcsr2002.pdf
| access-date = 2009-02-18
| year = 2002
| archive-url = https://web.archive.org/web/20110723104427/http://klaus.e175.net/emcsr2002.pdf
| archive-date = 2011-07-23
| url-status = dead
}} artificial neural networks and swarm intelligence systems (ant colony optimization, bees algorithm, etc.).