Editing Swarm behaviour (section)

====Ants====
{{See also|Ant colony|Ant colony optimization algorithm|Ant mill|Ant robotics}}
[[File:Red weaver ants transporting a dead gecko, in Laos (video).webm|thumb|right|A swarm of weaver ants (''[[Oecophylla smaragdina]]'') transporting a dead gecko]]

Individual [[ants]] do not exhibit complex behaviours, yet a colony of ants collectively achieves complex tasks such as constructing nests, taking care of their young, building bridges and [[foraging]] for food. A colony of ants can collectively select (i.e. send most workers towards) the best, or closest, food source from several in the vicinity.<ref>{{cite journal |last1=Czaczkes|first1=T.J.|last2=Grüter|first2=C.|last3=Ratnieks|first3=F. L. W.|title=Trail pheromones: an integrative view of their role in colony organisation|journal=Annual Review of Entomology|date=2015|volume=60|pages=581–599|doi=10.1146/annurev-ento-010814-020627|pmid=25386724|s2cid=37972066|doi-access=free}}</ref> Such collective decisions are achieved using positive feedback mechanisms. Selection of the best food source is achieved by ants following two simple rules. First, ants which find food return to the nest depositing a [[pheromone]] chemical. More pheromone is laid for higher quality food sources.<ref>{{cite journal |last1=Beckers|first1=R.|last2=Deneubourg|first2=J. L.|last3=Goss|first3=S|title=Modulation of trail laying in the ant Lasius niger (Hymenoptera: Formicidae) and its role in the collective selection of a food source|journal=Journal of Insect Behavior|date=1993|volume=6|issue=6|pages=751–759|doi=10.1007/BF01201674|bibcode=1993JIBeh...6..751B |citeseerx=10.1.1.161.9541|s2cid=14670150}}</ref> Thus, if two equidistant food sources of different qualities are found simultaneously, the pheromone trail to the better one will be stronger. Ants in the nest follow another simple rule, to favor stronger trails, on average. More ants then follow the stronger trail, so more ants arrive at the high quality food source, and a positive feedback cycle ensures, resulting in a collective decision for the best food source. If there are two paths from the ant nest to a food source, then the colony usually selects the shorter path. This is because the ants that first return to the nest from the food source are more likely to be those that took the shorter path. More ants then retrace the shorter path, reinforcing the pheromone trail.<ref>{{cite journal |last1=Goss|first1=S.|last2=Aron|first2=S.|last3=Deneubourg|first3=J. L.|last4=Pasteels|first4=J. M.|title=Self-organized shortcuts in the Argentine ant|journal=Naturwissenschaften|date=1989|volume=76|issue=12|pages=579–581|doi=10.1007/BF00462870|bibcode=1989NW.....76..579G|s2cid=18506807|url=https://dipot.ulb.ac.be/dspace/bitstream/2013/19271/1/042GossNaturwissenschaften89.pdf}}</ref>

[[Army ant]]s, unlike most ant species, do not construct permanent nests; an army ant colony moves almost incessantly over the time it exists, remaining in an essentially perpetual state of swarming. Several lineages have independently evolved the same basic behavioural and ecological syndrome, often referred to as "legionary behaviour", and may be an example of [[convergent evolution]].<ref name=brady2003>{{Cite journal |last1= Brady |first1= Seán G. |title = Evolution of the army ant syndrome: The origin and long-term evolutionary stasis of a complex of behavioral and reproductive adaptations |journal= Proceedings of the National Academy of Sciences of the United States of America |volume= 100 |issue = 11 |pages= 6575–9 |date=2003 |pmid= 12750466 |pmc= 164488 |doi= 10.1073/pnas.1137809100|bibcode= 2003PNAS..100.6575B |doi-access= free }}</ref>

The successful techniques used by [[ant colonies]] have been studied in computer science and [[robotics]] to produce [[distributed system|distributed]] and [[fault-tolerant system]]s for solving problems. This area of [[biomimetics]] has led to studies of ant locomotion, search engines that make use of "foraging trails", fault-tolerant storage and [[:Category:Networking algorithms|networking algorithms]].<ref name="SANdisk">{{cite book |vauthors=Dicke E, Byde A, Cliff D, Layzell P |year=2004 |chapter=An ant-inspired technique for storage area network design |title=Proceedings of Biologically Inspired Approaches to Advanced Information Technology: First International Workshop, BioADIT 2004 LNCS 3141 |url=https://archive.org/details/biologicallyinsp2004ijsp |url-access=limited |pages=[https://archive.org/details/biologicallyinsp2004ijsp/page/n378 364]–379 |publisher=Springer |isbn=9783540233398 |editor1=A. J. Ispeert |editor2=M. Murata |editor3=N. Wakamiya}}</ref>