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Emergent Sensing of Complex Environments by Mobile Animal Groups
Author(s) -
Andrew M. Berdahl,
Colin J. Torney,
Christos C. Ioannou,
Jolyon J. Faria,
Iain D. Couzin
Publication year - 2013
Publication title -
science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 12.556
H-Index - 1186
eISSN - 1095-9203
pISSN - 0036-8075
DOI - 10.1126/science.1225883
Subject(s) - pooling , collective intelligence , collective behavior , mechanism (biology) , imperfect , group behavior , computer science , social group , ecology , cognitive psychology , psychology , data science , artificial intelligence , biology , social psychology , sociology , physics , linguistics , philosophy , quantum mechanics , anthropology
The capacity for groups to exhibit collective intelligence is an often-cited advantage of group living. Previous studies have shown that social organisms frequently benefit from pooling imperfect individual estimates. However, in principle, collective intelligence may also emerge from interactions between individuals, rather than from the enhancement of personal estimates. Here, we reveal that this emergent problem solving is the predominant mechanism by which a mobile animal group responds to complex environmental gradients. Robust collective sensing arises at the group level from individuals modulating their speed in response to local, scalar, measurements of light and through social interaction with others. This distributed sensing requires only rudimentary cognition and thus could be widespread across biological taxa, in addition to being appropriate and cost-effective for robotic agents.

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