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.

24The social fine structure of a population plays a central role in ecological and 25 evolutionary processes. Whilst many studies have investigated how morphological traits 26 such as size affect social structure of populations, comparatively little is known about the 27 influence of behaviours such as boldness and shyness. Using information on social 28 interactions in a wild population of Trinidadian guppies (Poecilia reticulata) we construct 29 a social network. For each individual in the network we quantify its behavioural 30 phenotype using two measures of boldness, predator inspection tendency, a repeatable 31 and reliably measured behaviour well studied in the context of co-operation, and shoaling 32 tendency. We observe striking heterogeneity in contact patterns, with strong ties being 33 positively assorted, and weak ties negatively assorted by our measured behavioural traits. 34Moreover, shy fish had more network connections than bold fish and these were on 35 average stronger. In other words, social fine-structure is strongly influenced by 36 behavioural trait. We assert that such structure will have implications for the outcome of 37 selection on behavioural traits and we speculate that the observed positive assortment 38 may act as an amplifier of selection contributing to the maintenance of co-operation 39 during predator inspection.

Nature is rich with many different examples of the cohesive motion of animals. Previous attempts to model collective motion have primarily focused on group behaviours of identical individuals. In contrast, we put our emphasis on modelling the contributions of different individual-level characteristics within such groups by using stochastic asynchronous updating of individual positions and orientations. Our model predicts that higher updating frequency, which we relate to perceived threat, leads to more synchronized group movement, with speed and nearest-neighbour distributions becoming more uniform. Experiments with three-spined sticklebacks (Gasterosteus aculeatus) that were exposed to different threat levels provide strong empirical support for our predictions. Our results suggest that the behaviour of fish (at different states of agitation) can be explained by a single parameter in our model: the updating frequency. We postulate a mechanism for collective behavioural changes in different environment-induced contexts, and explain our findings with reference to confusion and oddity effects.

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