Allelomimetic synchronization in Merino sheep

Gautrais, Jacques; Michelena, Pablo; Sibbald, A. R.; Bon, Richard; Deneubourg, Jean‐Louis

doi:10.1016/j.anbehav.2007.02.020

Cited by 85 publications

(80 citation statements)

References 32 publications

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“…The model is based on rules of mimetism/cohesion (Markov chain process) described in several studies on collective phenom ena (Amé et al, 2006;Gautrais et al, 2007;Dussutour et al, 2005). In this model, the probability of an individual joining a collective movement in one direction (the future sub group) depends on the number but also the strength of relationships it has with the individuals already in this direction.…”

Section: State Variables and Scalesmentioning

confidence: 99%

Group size, grooming and fission in primates: A modeling approach based on group structure

Sueur

Deneubourg²,

Petit

et al. 2011

Journal of Theoretical Biology

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a b s t r a c tIn social animals, fission is a common mode of group proliferation and dispersion and may be affected by genetic or other social factors. Sociality implies preserving relationships between group members. An increase in group size and/or in competition for food within the group can result in decrease certain social interactions between members, and the group may split irreversibly as a consequence. One individual may try to maintain bonds with a maximum of group members in order to keep group cohesion, i.e. proximity and stable relationships. However, this strategy needs time and time is often limited. In addition, previous studies have shown that whatever the group size, an individual interacts only with certain grooming partners. There, we develop a computational model to assess how dynamics of group cohesion are related to group size and to the structure of grooming relationships. Groups' sizes after simulated fission are compared to observed sizes of 40 groups of primates. Results showed that the relationship between grooming time and group size is dependent on how each individual attributes grooming time to its social partners, i.e. grooming a few number of preferred partners or grooming equally or not all partners. The number of partners seemed to be more important for the group cohesion than the grooming time itself. This structural constraint has important consequences on group sociality, as it gives the possibility of competition for grooming partners, attraction for high ranking individuals as found in primates' groups. It could, however, also have implications when considering the cognitive capacities of primates.

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Section: State Variables and Scalesmentioning

confidence: 99%

Group size, grooming and fission in primates: A modeling approach based on group structure

Sueur

Deneubourg²,

Petit

et al. 2011

Journal of Theoretical Biology

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“…Analysis of gaze behavior across observers suggests that the greater collective integration benefits for visual search arise from an interaction between the foveated properties of the human visual system (high foveal acuity and low peripheral acuity) and observers' nonexhaustive search patterns, and can be predicted by an extended signal detection theory framework with trial to trial sampling from a varying mixture of high and low target detectabilities across observers (SDT-MIX). These findings advance our theoretical understanding of how to predict and enhance the wisdom of crowds for real world search tasks and could apply more generally to any decision-making task for which the minority of group members with high expertise varies from decision to decision.group decision rules | signal detection theory | ideal observer analyses | wisdom of crowds G roups of insects (1-4), fish (5-7), birds (8-10), mammals (11)(12)(13)(14), and primates (15-18) have been shown to aggregate their individual judgments into group decisions for various tasks (19,20). Although some groups seem to have leaders who make decisions alone on behalf of their groups (17,(21)(22)(23), it is difficult for individuals to outperform even simple aggregations of the entire group's individual judgments (4,7,9,10,19,(24)(25)(26).…”

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confidence: 99%

“…group decision rules | signal detection theory | ideal observer analyses | wisdom of crowds G roups of insects (1)(2)(3)(4), fish (5-7), birds (8)(9)(10), mammals (11)(12)(13)(14), and primates (15)(16)(17)(18) have been shown to aggregate their individual judgments into group decisions for various tasks (19,20). Although some groups seem to have leaders who make decisions alone on behalf of their groups (17,(21)(22)(23), it is difficult for individuals to outperform even simple aggregations of the entire group's individual judgments (4,7,9,10,19,(24)(25)(26).…”

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confidence: 99%

The wisdom of crowds for visual search

Juni

Eckstein

2017

Proc. Natl. Acad. Sci. U.S.A.

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Decision-making accuracy typically increases through collective integration of people's judgments into group decisions, a phenomenon known as the wisdom of crowds. For simple perceptual laboratory tasks, classic signal detection theory specifies the upper limit for collective integration benefits obtained by weighted averaging of people's confidences, and simple majority voting can often approximate that limit. Life-critical perceptual decisions often involve searching large image data (e.g., medical, security, and aerial imagery), but the expected benefits and merits of using different pooling algorithms are unknown for such tasks. Here, we show that expected pooling benefits are significantly greater for visual search than for single-location perceptual tasks and the prediction given by classic signal detection theory. In addition, we show that simple majority voting obtains inferior accuracy benefits for visual search relative to averaging and weighted averaging of observers' confidences. Analysis of gaze behavior across observers suggests that the greater collective integration benefits for visual search arise from an interaction between the foveated properties of the human visual system (high foveal acuity and low peripheral acuity) and observers' nonexhaustive search patterns, and can be predicted by an extended signal detection theory framework with trial to trial sampling from a varying mixture of high and low target detectabilities across observers (SDT-MIX). These findings advance our theoretical understanding of how to predict and enhance the wisdom of crowds for real world search tasks and could apply more generally to any decision-making task for which the minority of group members with high expertise varies from decision to decision.group decision rules | signal detection theory | ideal observer analyses | wisdom of crowds G roups of insects (1-4), fish (5-7), birds (8-10), mammals (11)(12)(13)(14), and primates (15-18) have been shown to aggregate their individual judgments into group decisions for various tasks (19,20). Although some groups seem to have leaders who make decisions alone on behalf of their groups (17,(21)(22)(23), it is difficult for individuals to outperform even simple aggregations of the entire group's individual judgments (4,7,9,10,19,(24)(25)(26). Perhaps that is why humans often make important decisions as a group (27-29), even if the only expedient (30, 31) but effective (24, 31-34) group decision mechanism is to use the simple majority voting rule (35).Previous human studies have shown that combining people's judgments into group decisions can lead to accuracy benefits in various domains, such as estimation (36-38), detection (34,(39)(40)(41)(42)(43)(44), identification (45-47), and prediction (46, 48-52), a phenomenon known as the wisdom of crowds (53). For artificial tasks, where perceptual decisions are limited only by noise that is internal to each observer's brain (i.e., no external noise), the maximum wisdom of crowd benefits are specified by the idealized signal dete...

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“…However, the concept of social facilitation has been introduced to explain why animals start an activity, not why they stop an activity. We evaluated only lying behaviour, that is, the absence of an activity and to our knowledge social facilitation has never been reported in cattle in this context (in sheep, see Gautrais et al, 2007). Therefore, the environmental stimuli provided by the timing of milking (conventional milking: simultaneous for all cows or automatic milking: spread throughout the day across cows) or feeding were likely insufficient to modify the lying behaviour of cows, although all the cows milked automatically could not eat at the same time (due to less feeding places than for conventionally milked cows).…”

Section: Discussionmentioning

confidence: 99%

A note on overdispersion as an index of behavioural synchrony: a pilot study in dairy cows

Raussi

Jauhiainen

Saastamoinen

et al. 2011

Animal

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We developed a method for studying the synchrony of behaviour based on calculations of overdispersion of a binomial process. The lying behaviour of cows was investigated under two different housing units inside the same barn. The first unit housed 30 cows undergoing conventional milking and the second unit housed 27 cows undergoing automatic milking. The lying behaviour of the cows was observed over 3 weeks in 12 periods of 6 h each. Every 5 min, we counted the number of cows lying down in the cubicles. As external cues, like feeding and conventional milking, can promote synchrony in dairy cows, we expected that cows conventionally milked would show more behavioural synchrony than automatically milked cows. Cows lied down synchronously in both units (overdispersion 1.67, P , 0.01). Lying synchrony tended to be slightly bigger in automatically than in conventionally milked cows (overdispersion 1.76 v. 1.58, P 5 0.09), although the proportion of cows lying down was on average greater in conventionally than in automatically milked cows (60.7% v. 45.6%). This suggests that synchronized lying behaviour in cows is a constant phenomenon that depends on social facilitation rather than on external cues. The overdispersion index appears to be a useful tool for studying the synchrony of animal behaviour when observations are made at the group level.

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Allelomimetic synchronization in Merino sheep

Cited by 85 publications

References 32 publications

Group size, grooming and fission in primates: A modeling approach based on group structure

Group size, grooming and fission in primates: A modeling approach based on group structure

The wisdom of crowds for visual search

A note on overdispersion as an index of behavioural synchrony: a pilot study in dairy cows

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