Individual- and group-level mechanisms of collective behaviour in weaver ants

<p dir="ltr">From living cells to global climate and social networks, complex systems are the fundamental building blocks of the world we inhabit. The behaviour of these systems emerges solely from the interactions among their components, without central control. This makes them extremely adaptive to environmental conditions and exceptionally resilient to individual points of failure, but also incredibly difficult to predict. Recent advances in science and technology have opened the opportunity to develop distributed solutions for relevant real-world problems – such as resource management, social networks and biotechnology – making the study of complex systems more important than ever. Natural systems have long been a source of inspiration for human-made systems, having evolved over millions of years to solve the challenges posed by their habitat. Insight into their functioning is essential to expand our understanding of the world we live in and to advance our technological evolution. Despite this, the intrinsic complexity of these systems has so far limited our ability to identify the mechanisms that allow several interacting units to generate apparently sophisticated global behaviours.</p><p dir="ltr">Ant colonies offer a rare glimpse into the functioning of complex systems, allowing to draw direct links between the local and global behaviour of the group. In my thesis I exploited the experimental amenability of ant groups to (1) characterise the local mechanisms that allow ants to perform collective actions; (2) understand how ants make collective decisions under different information availability scenarios; and (3) identify the dynamics that underlie optimisation in the absence of centralised control. To this aim I investigated the collective behaviour of the weaver ant Oecophylla smaragdina, which exhibits one of the most impressive arrays of cooperative behaviours and communication abilities within the social insects.</p><p dir="ltr">Combining behavioural experiments with theoretical modelling, I demonstrated that weaver ants perform collective tasks by simply pooling together the decisions of several group members, with minimal interindividual interactions. Each ant makes an independent assessment of the stimuli in the surrounding environment, and the collective behaviour of the group emerges from the combination of the assessments made by several individuals. Using this simple behavioural strategy weaver ants were able to make adaptive decisions under information uncertainty, to quickly resolve contrasting preferences among group members, and to optimise the performance of their collective actions.</p><p dir="ltr">My work sheds light into the individual-level dynamics governing two well-known collective behaviours of Oecophylla ants, namely cooperative transport and self-assembly, which have been seldom studied before. My findings align with the current theories of complex systems science, showing that complex group behaviours can be explained through simple behavioural rules that only require local information, without the need to invoke advanced cognition or sophisticated social feedbacks. The mechanisms outlined in this thesis have the potential to inspire distributed algorithms for artificial decentralised systems, and may be especially relevant for swarm robotics applications where scenarios of uncertainty and intragroup conflict are most likely to be encountered.</p>