2013年8月15日木曜日

Emergent Sensing of Complex Environments by Mobile Animal Groups

Andrew Berdahl1, Colin J. Torney, Christos C. Ioannou, Jolyon J. Faria, Iain D. Couzin
Science 1 February 2013:
Vol. 339 no. 6119 pp. 574-576

群れがどのように「最適な場所」を探し当てるのか?
魚の群れを用いた実験とコンピュータ・シミュレーションを組み合わせることにより、
各個体が「環境の情報」と「多個体の移動方向の情報」を使って自分の移動方向/スピードを決める時、群れ全体として(個体単独の場合と比べて)よりうまく最適な場所を探し当てられる、ことが分かった。

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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