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Biomedical subjects

David J T Sumpter

Publications and source records attributed to David J T Sumpter.

3 recordsLinked to original sources

From compromise to leadership in pigeon homing.

A central problem faced by animals traveling in groups is how navigational decisions by group members are integrated, especially when members cannot assess which individuals are best informed or have conflicting information or interests . Pigeons are now known to recapitulate faithfully their individually distinct habitual routes home , and this provides a novel paradigm for investigating collective decisions during flight under varying levels of interindividual conflict. Using high-precision GPS tracking of pairs of pigeons, we found that if conflict between two birds' directional preferences was small, individuals averaged their routes, whereas if conflict rose over a critical threshold, either the pair split or one of the birds became the leader. Modeling such paired decision-making showed that both outcomes-compromise and leadership-could emerge from the same set of simple behavioral rules. Pairs also navigated more efficiently than did the individuals of which they were composed, even though leadership was not necessarily assumed by the more efficient bird. In the context of mass migration of birds and other animals, our results imply that simple self-organizing rules can produce behaviors that improve accuracy in decision-making and thus benefit individuals traveling in groups .

Animal Migration↗

A tunable algorithm for collective decision-making.

Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.

Algorithms↗

Information flow, opinion polling and collective intelligence in house-hunting social insects.

The sharing and collective processing of information by certain insect societies is one of the reasons that they warrant the superlative epithet 'super-organisms' (Franks 1989, Am. Sci. 77, 138-145). We describe a detailed experimental and mathematical analysis of information exchange and decision-making in, arguably, the most difficult collective choices that social insects face: namely, house hunting by complete societies. The key issue is how can a complete colony select the single best nest-site among several alternatives? Individual scouts respond to the diverse information they have personally obtained about the quality of a potential nest-site by producing a recruitment signal. The colony then deliberates over (i.e. integrates) different incoming recruitment signals associated with different potential nest-sites to achieve a well-informed collective decision. We compare this process in honeybees and in the ant Leptothorax albipennis. Notwithstanding many differences - for example, honeybee colonies have 100 times more individuals than L. albipennis colonies - there are certain similarities in the fundamental algorithms these societies appear to employ when they are house hunting. Scout honeybees use the full power of the waggle dance to inform their nest-mates about the distance and direction of a potential nest-site (and they indicate the quality of a nest-site indirectly through the vigour of their dance), and yet individual bees perhaps only rarely make direct comparisons of such sites. By contrast, scouts from L. albipennis colonies often compare nest-sites, but they cannot directly inform one another of their estimation of the quality of a potential site. Instead, they discriminate between sites by initiating recruitment sooner to better ones. Nevertheless, both species do make use of forms of opinion polling. For example, scout bees that have formerly danced for a certain site cease such advertising and monitor the dances of others at random. That is, they act without prejudice. They neither favour nor disdain dancers that advocate the site they had formerly advertised or the alternatives. Thus, in general the bees are less well informed than they would be if they systematically monitored dances for alternative sites rather than spending their time reprocessing information they already have. However, as a result of their lack of prejudice, less time overall will be wasted in endless debate among stubborn and potentially biased bees. Among the ants, the opinions of nest-mates are also pooled effectively when scouts use a threshold population of their nest-mates present in a new nest-site as a cue to switch to more rapid recruitment. Furthermore, the ants' reluctance to begin recruiting to poor nest-sites means that more time is available for the discovery and direct comparison of alternatives. Likewise, the retirement of honeybee scouts from dancing for a given site allows more time for other scouts to find potentially better sites. Thus, both the ants and the bees have time-lags built into their decision-making systems that should facilitate a compromise between thorough surveys for good nest-sites and relatively rapid decisions. We have also been able to show that classical mathematical models can illuminate the processes by which colonies are able to achieve decisions that are relatively swift and very well informed.

Animal Communication↗