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Ant groups optimally amplify the effect of transiently informed individuals.

Gelblum A, Pinkoviezky I, Fonio E, Ghosh A, Gov N, Feinerman O - Nat Commun (2015)

Bottom Line: A downside of behavioural conformism is that it may decrease the group's responsiveness to external information.Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions.Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel.

ABSTRACT
To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge.

No MeSH data available.


Related in: MedlinePlus

Microscopic model.(a) Model sketch including the possible transitions for non-informed individual ants. (b–e) The four model parameters were set by fitting experimental data of b. The distribution of the object's velocity (projected on an arbitrary direction) in periods of continuous motion (N=56,030 frames). (c) Correlation distance functions (N=17 trajectories). (d) Median speed (N=56,030 frames). (e) Median angular speed (N=56,030 frames). In each of these panels, the coloured lines represent the experimental data for ants transporting a load in the absence of informed ants. The solid black lines denote the results of our model. Error bars in c are the maxima and minima of correlation functions produced by partitioning the data into four parts. Error bars in d and e are the s.d. of a distribution of medians calculated for 1,000 samples bootstrapped from the data.
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f3: Microscopic model.(a) Model sketch including the possible transitions for non-informed individual ants. (b–e) The four model parameters were set by fitting experimental data of b. The distribution of the object's velocity (projected on an arbitrary direction) in periods of continuous motion (N=56,030 frames). (c) Correlation distance functions (N=17 trajectories). (d) Median speed (N=56,030 frames). (e) Median angular speed (N=56,030 frames). In each of these panels, the coloured lines represent the experimental data for ants transporting a load in the absence of informed ants. The solid black lines denote the results of our model. Error bars in c are the maxima and minima of correlation functions produced by partitioning the data into four parts. Error bars in d and e are the s.d. of a distribution of medians calculated for 1,000 samples bootstrapped from the data.

Mentions: On the basis of the experimental properties outlined above, we constructed a theoretical model as specified in Fig. 3a, Supplementary Notes 12–14, Supplementary Fig. 7 and the Methods section. In short, the model is based on the minimal assumption that carriers interact uniquely through local forces transmitted to them by the load31. Informed ants are assumed to ignore these forces and attempt to pull the load in the correct nest-bound direction. Our experimental data suggests that the information held by ants deteriorates after they had been attached for a certain period (Fig. 2a,c). For simplicity, the model assumes that these ants become completely uninformed.


Ant groups optimally amplify the effect of transiently informed individuals.

Gelblum A, Pinkoviezky I, Fonio E, Ghosh A, Gov N, Feinerman O - Nat Commun (2015)

Microscopic model.(a) Model sketch including the possible transitions for non-informed individual ants. (b–e) The four model parameters were set by fitting experimental data of b. The distribution of the object's velocity (projected on an arbitrary direction) in periods of continuous motion (N=56,030 frames). (c) Correlation distance functions (N=17 trajectories). (d) Median speed (N=56,030 frames). (e) Median angular speed (N=56,030 frames). In each of these panels, the coloured lines represent the experimental data for ants transporting a load in the absence of informed ants. The solid black lines denote the results of our model. Error bars in c are the maxima and minima of correlation functions produced by partitioning the data into four parts. Error bars in d and e are the s.d. of a distribution of medians calculated for 1,000 samples bootstrapped from the data.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4525283&req=5

f3: Microscopic model.(a) Model sketch including the possible transitions for non-informed individual ants. (b–e) The four model parameters were set by fitting experimental data of b. The distribution of the object's velocity (projected on an arbitrary direction) in periods of continuous motion (N=56,030 frames). (c) Correlation distance functions (N=17 trajectories). (d) Median speed (N=56,030 frames). (e) Median angular speed (N=56,030 frames). In each of these panels, the coloured lines represent the experimental data for ants transporting a load in the absence of informed ants. The solid black lines denote the results of our model. Error bars in c are the maxima and minima of correlation functions produced by partitioning the data into four parts. Error bars in d and e are the s.d. of a distribution of medians calculated for 1,000 samples bootstrapped from the data.
Mentions: On the basis of the experimental properties outlined above, we constructed a theoretical model as specified in Fig. 3a, Supplementary Notes 12–14, Supplementary Fig. 7 and the Methods section. In short, the model is based on the minimal assumption that carriers interact uniquely through local forces transmitted to them by the load31. Informed ants are assumed to ignore these forces and attempt to pull the load in the correct nest-bound direction. Our experimental data suggests that the information held by ants deteriorates after they had been attached for a certain period (Fig. 2a,c). For simplicity, the model assumes that these ants become completely uninformed.

Bottom Line: A downside of behavioural conformism is that it may decrease the group's responsiveness to external information.Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions.Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel.

ABSTRACT
To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge.

No MeSH data available.


Related in: MedlinePlus