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{{short description|Algorithm exhibiting emergent behavior}}
An '''emergent algorithm''' is an [[algorithm]] that has the following characteristics:
An '''emergent algorithm''' is an [[algorithm]] that exhibits [[Emergence|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 logic|fuzzy]] motion controllers used to adapt robot movement in response to environmental obstacles.<ref>[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)</ref>


An '''emergent algorithm''' has the following characteristics: {{dubious|date=May 2013}}
* it achieves predictable [[global effect]]s;
* it does not require [[global visibility]];
* it does not assume any kind of [[centralized control]];
* it is self-stabilizing.


* it achieves predictable [[global effect]]s
'''See also'''
* it does not require [[global visibility]]
* [[genetic algorithm]]
* it does not assume any kind of [[centralized control]]
* [[heuristic]]
* it is [[self-stabilization|self-stabilizing]]


Other examples of emergent algorithms and models include [[cellular automata]],<ref>{{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
}}</ref> [[artificial neural networks]] and [[swarm intelligence]] systems ([[ant colony optimization]], [[bees algorithm]], etc.).


== See also ==
'''External links'''
* [[AI alignment]]
* [http://www.cert.org/archive/html/emergent-algor.html Emergent Algorithms: A New Method for Enhancing Survivability in Unbounded Systems]
* [[Artificial intelligence detection software]]
* [[Emergence]]
* [[Evolutionary computation]]
* [[Fuzzy logic]]
* [[Genetic algorithm]]
* [[Heuristic]]

==References==

<references/>

{{DEFAULTSORT:Emergent Algorithm}}
[[Category:Emergence|Algorithm]]
[[Category:Heuristic algorithms]]
[[Category:Algorithms]]
[[Category:Artificial intelligence]]
[[Category:Cybernetics]]


{{chaos-stub}}

Latest revision as of 12:25, 13 September 2023

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.[1]

An emergent algorithm has the following characteristics: [dubiousdiscuss]

Other examples of emergent algorithms and models include cellular automata,[2] artificial neural networks and swarm intelligence systems (ant colony optimization, bees algorithm, etc.).

See also[edit]

References[edit]

  1. ^ 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)
  2. ^ Brunner, Klaus A. (2002). "What's emergent in Emergent Computing?" (PDF). Cybernetics and Systems 2002: Proceedings of the 16th European Meeting on Cybernetics and Systems Research. Vol. 1. Vienna. pp. 189–192. Archived from the original (PDF) on 2011-07-23. Retrieved 2009-02-18.