‘Infotaxis’ as a strategy for searching without gradients

Vergassola, Massimo; Villermaux, Emmanuel; Shraiman, Boris I.

doi:10.1038/nature05464

Cited by 763 publications

(847 citation statements)

References 24 publications

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“…Here, the cue is independently sampled by the group members, and each member has a probability r of receiving correct information from the cue. However, water is subjected to currents and turbulence, which can globally affect group members' probability of receiving correct information from the cue [44][45][46]. We consider that with a probability g, the water current is such that the probability that each individual receives correct information increases to r þ 1, whereas with probability 1 2 g, the probability decreases to r 2 1 ( figure 3a).…”

Section: (E) Modelling Correlated Fluctuations In Cue Reliabilitymentioning

confidence: 99%

Decision accuracy in complex environments is often maximized by small group sizes

2014

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Individuals in groups, whether composed of humans or other animal species, often make important decisions collectively, including avoiding predators, selecting a direction in which to migrate and electing political leaders. Theoretical and empirical work suggests that collective decisions can be more accurate than individual decisions, a phenomenon known as the 'wisdom of crowds'. In these previous studies, it has been assumed that individuals make independent estimates based on a single environmental cue. In the real world, however, most cues exhibit some spatial and temporal correlation, and consequently, the sensory information that near neighbours detect will also be, to some degree, correlated. Furthermore, it may be rare for an environment to contain only a single informative cue, with multiple cues being the norm. We demonstrate, using two simple models, that taking this natural complexity into account considerably alters the relationship between group size and decision-making accuracy. In only a minority of environments do we observe the typical wisdom of crowds phenomenon (whereby collective accuracy increases monotonically with group size). When the wisdom of crowds is not observed, we find that a finite, and often small, group size maximizes decision accuracy. We reveal that, counterintuitively, it is the noise inherent in these small groups that enhances their accuracy, allowing individuals in such groups to avoid the detrimental effects of correlated information while exploiting the benefits of collective decision-making. Our results demonstrate that the conventional view of the wisdom of crowds may not be informative in complex and realistic environments, and that being in small groups can maximize decision accuracy across many contexts.

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Section: (E) Modelling Correlated Fluctuations In Cue Reliabilitymentioning

confidence: 99%

Decision accuracy in complex environments is often maximized by small group sizes

2014

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“…size of plume quanta and distance between these quanta; and the ability to trace the plume back to its source, the ultimate goal of any seeking behaviour (e.g. , Lemon and Getz 1998, Moore 1994, Vergassola et al 2007, Vickers 2006, Willis and Arbas 1991. The two main temporal coding regimes used in the periphery are phasic and tonic spiking response patterns ( Figure 5).…”

Section: Temporal Coding and Stimulus Frequencymentioning

confidence: 99%

Olfaction in vector-host interactions

Takken¹,

Knols²

2010

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confidence: 99%

Separating stretching from folding in fluid mixing

Kelley

Ouellette

2011

Nature Phys

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Fluid mixing controls many natural and industrial processes, including the spread of air pollution 1 , mass transfer and reactions in microfluidic devices 2,3 and the detection of odours or other chemical signals 4 . Strongly nonlinear flows enhance mixing by chaotic advection 5,6 , stretching and folding 7,8 fluid volumes. Though these processes have been studied in simple models 9,10 , stretching and folding are difficult to distinguish in real flows with complex spatiotemporal structure. Here we report measurements of these two distinct processes in a two-dimensional laboratory flow. We decouple stretching and folding using tools developed for analysing glassy solids 11 and colloids 12 , breaking fluid deformation into a linear, affine component (primarily stretching) and a nonlinear, non-affine component (primarily folding). Short-time deformation is dominated by stretching, whereas folding occurs only after fluid elements are elongated. The relative strength of the two processes depends strongly on space and time; foldingdominated regions are initially isolated, but later grow to fill space.Mixing is fundamentally a diffusion process: at the boundary of an impurity in a fluid, the concentration gradient is large and material flows until the gradient vanishes. Diffusion alone is inefficient for large-scale transport, such as is required in industrial mixers or observed in geophysical flow. Moving fluids, however, can greatly enhance mixing through chaotic advection 5,6 . As the fluid moves, the region containing the impurity is strongly deformed, the length of its boundary grows exponentially and diffusion becomes efficient. The key to understanding chaotic mixing, then, is the characterization of the deformation of fluid elements 8 . As first described by Reynolds 7 , this process is one of stretching, which increases the length of the interface, and folding, which constrains the fluid element to fill a finite region of space. These geometric processes are often studied in simple mathematical models such as the baker's or horseshoe maps 9,10 . Such models, however, differ from actual fluid flow in that they are discrete, periodic and highly idealized. Although stretching and folding have been described qualitatively in real flows 2,13,14 , they have not been quantitatively distinguished spatially, temporally or dynamically in flows with complex spatiotemporal structure.Deformation of a material volume consists of the relative motion, and potentially rearrangement, of infinitesimal fluid elements. These relative displacements can be broadly characterized as either affine-that is, some combination of rotation, shear, dilation or compression 15 -or non-affine. Affine deformation is linear, and can be represented by a matrix operator. Non-affine deformation is nonlinear, and generally consists of irreversible rearrangements of the constituent volume elements 11 . This distinction between affine and non-affine deformation has been used to study shear transformation zones and plasticity in metallic glasses 11,16 ...

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‘Infotaxis’ as a strategy for searching without gradients

Cited by 763 publications

References 24 publications

Decision accuracy in complex environments is often maximized by small group sizes

Decision accuracy in complex environments is often maximized by small group sizes

Olfaction in vector-host interactions

Separating stretching from folding in fluid mixing

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