Robustness of self-organised systems to changes in individual level behaviour: an example from real and simulated self-organised snail aggregations

Gray Williams,Mark Davies,Richard Stafford

doi:10.1038/npre.2009.3922.1

Gray Williams, Mark Davies + Show 1 more

Open Access

https://doi.org/10.1038/npre.2009.3922.1

Copy DOI

Abstract

AbstractPerfect behaviours that are optimal to the environment an agent operates within rarely exist in real animals or in robotic systems. The costs (be they biological or economic) of building sensors and processing the information they capture become excessive compared to the small advantages that occur from the modifications of behaviour. Many self-organised systems are thought to change their properties as a result of changes in individual behaviour. Here, using both natural systems and computer simulations, we demonstrate that intertidal snail aggregations slightly decrease in size when individuals forage for shorter periods due to hotter and more desiccating conditions – a non-optimal behaviour for the snails since aggregation reduces desiccation stress. However, this decrease only occurs in simple experimental systems (and simulations of these systems). When studied in their more complex natural environment, and when simulated in such an environment, using the same information-processing behaviours, no difference in aggregation behaviour was found between hot and cool days. These results give an indication of the robustness of self-organised systems to changes in individual-level behaviour. They demonstrate that information processing capabilities of self-organised groups may not need to be as great as for agents that perform solitary tasks, and also that oversimplified tests of swarm intelligence may not give a true indication of how tasks may be performed in a more complex environment.

Highlights

While behaviours in real animals are normally adaptive, increasing survival and reproduction [1], they are not normally perfect
If changes to individual behaviours occur, does the collective behaviour vary? We study this in both a natural system and a simulation of this system
Aggregations result from a process of self-organisation, essentially aggregations arise from chance encounters with other individuals, but these chance encounters are facilitated by following of mucus trails

Summary

Introduction

While behaviours in real animals are normally adaptive, increasing survival and reproduction [1], they are not normally perfect. Many birds are unable to recognise the eggs of brood parasites, such as cuckoos [2], insects that manipulate the sex ratio of their offspring tend to pick suboptimal ratios at low foundress densities [3] and animals do not always select optimal habitats in which to breed, in terms of resource allocation [4]. To increase the optimality of behaviours requires bigger and more complex sensory and nervous systems. Increasing the ability of a robot to complete a task can be achieved by more technology, more sensors, more computational power etc., but these processes incur costs – be they economic, or physically restrictive in terms of weight, size or power consumption [11]

Methods

Results

Conclusion