scholarly journals Information transfer in moving animal groups

2008 ◽  
Vol 127 (2) ◽  
pp. 177-186 ◽  
Author(s):  
David Sumpter ◽  
Jerome Buhl ◽  
Dora Biro ◽  
Iain Couzin
2019 ◽  
Vol 4 (28) ◽  
pp. eaau7897 ◽  
Author(s):  
Frank Bonnet ◽  
Rob Mills ◽  
Martina Szopek ◽  
Sarah Schönwetter-Fuchs ◽  
José Halloy ◽  
...  

Self-organized collective behavior has been analyzed in diverse types of gregarious animals. Such collective intelligence emerges from the synergy between individuals, which behave at their own time and spatial scales and without global rules. Recently, robots have been developed to collaborate with animal groups in the pursuit of better understanding their decision-making processes. These biohybrid systems make cooperative relationships between artificial systems and animals possible, which can yield new capabilities in the resulting mixed group. However, robots are currently tailor-made to successfully engage with one animal species at a time. This limits the possibilities of introducing distinct species-dependent perceptual capabilities and types of behaviors in the same system. Here, we show that robots socially integrated into animal groups of honeybees and zebrafish, each one located in a different city, allowing these two species to interact. This interspecific information transfer is demonstrated by collective decisions that emerge between the two autonomous robotic systems and the two animal groups. The robots enable this biohybrid system to function at any distance and operates in water and air with multiple sensorimotor properties across species barriers and ecosystems. These results demonstrate the feasibility of generating and controlling behavioral patterns in biohybrid groups of multiple species. Such interspecies connections between diverse robotic systems and animal species may open the door for new forms of artificial collective intelligence, where the unrivaled perceptual capabilities of the animals and their brains can be used to enhance autonomous decision-making, which could find applications in selective “rewiring” of ecosystems.


2013 ◽  
Vol 23 (17) ◽  
pp. R709-R711 ◽  
Author(s):  
Ariana Strandburg-Peshkin ◽  
Colin R. Twomey ◽  
Nikolai W.F. Bode ◽  
Albert B. Kao ◽  
Yael Katz ◽  
...  

2021 ◽  
Vol 9 ◽  
Author(s):  
Winnie Poel ◽  
Claudia Winklmayr ◽  
Pawel Romanczuk

In human and animal groups, social interactions often rely on the transmission of information via visual observation of the behavior of others. These visual interactions are governed by the laws of physics and sensory limits. Individuals appear smaller when far away and thus become harder to detect visually, while close by neighbors tend to occlude large areas of the visual field and block out interactions with individuals behind them. Here, we systematically study the effect of a group’s spatial structure, its density as well as polarization and aspect ratio of the physical bodies, on the properties of static visual interaction networks. In such a network individuals are connected if they can see each other as opposed to other interaction models such as metric or topological networks that omit these limitations due to the individual’s physical bodies. We find that structural parameters of the visual networks and especially their dependence on spatial group density are fundamentally different from the two other types. This results in characteristic deviations in information spreading which we study via the dynamics of two generic SIR-type models of social contagion on static visual and metric networks. We expect our work to have implications for the study of animal groups, where it could inform the study of functional benefits of different macroscopic states. It may also be applicable to the construction of robotic swarms communicating via vision or for understanding the spread of panics in human crowds.


2019 ◽  
Vol 42 ◽  
Author(s):  
Amanda R. Ridley ◽  
Melanie O. Mirville

Abstract There is a large body of research on conflict in nonhuman animal groups that measures the costs and benefits of intergroup conflict, and we suggest that much of this evidence is missing from De Dreu and Gross's interesting article. It is a shame this work has been missed, because it provides evidence for interesting ideas put forward in the article.


Author(s):  
David A. Grano ◽  
Kenneth H. Downing

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.


Author(s):  
D. Van Dyck

An (electron) microscope can be considered as a communication channel that transfers structural information between an object and an observer. In electron microscopy this information is carried by electrons. According to the theory of Shannon the maximal information rate (or capacity) of a communication channel is given by C = B log2 (1 + S/N) bits/sec., where B is the band width, and S and N the average signal power, respectively noise power at the output. We will now apply to study the information transfer in an electron microscope. For simplicity we will assume the object and the image to be onedimensional (the results can straightforwardly be generalized). An imaging device can be characterized by its transfer function, which describes the magnitude with which a spatial frequency g is transferred through the device, n is the noise. Usually, the resolution of the instrument ᑭ is defined from the cut-off 1/ᑭ beyond which no spadal information is transferred.


2009 ◽  
Vol 14 (1) ◽  
pp. 78-89 ◽  
Author(s):  
Kenneth Hugdahl ◽  
René Westerhausen

The present paper is based on a talk on hemispheric asymmetry given by Kenneth Hugdahl at the Xth European Congress of Psychology, Praha July 2007. Here, we propose that hemispheric asymmetry evolved because of a left hemisphere speech processing specialization. The evolution of speech and the need for air-based communication necessitated division of labor between the hemispheres in order to avoid having duplicate copies in both hemispheres that would increase processing redundancy. It is argued that the neuronal basis of this labor division is the structural asymmetry observed in the peri-Sylvian region in the posterior part of the temporal lobe, with a left larger than right planum temporale area. This is the only example where a structural, or anatomical, asymmetry matches a corresponding functional asymmetry. The increase in gray matter volume in the left planum temporale area corresponds to a functional asymmetry of speech processing, as indexed from both behavioral, dichotic listening, and functional neuroimaging studies. The functional anatomy of the corpus callosum also supports such a view, with regional specificity of information transfer between the hemispheres.


2006 ◽  
Author(s):  
Ayse P. Gurses ◽  
Yan Xiao ◽  
Paul Gorman ◽  
Brian Hazlehurst ◽  
Grant Bochicchio ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document