The Wisdom of the Acorn: Social Foraging in Temnothorax ants

abstract: The coordination of group behavior in the social insects is representative of a broader phenomenon in nature, emergent biological complexity. In such systems, it is believed that large-scale patterns result from the interaction of relatively simple subunits. This dissertation involved the study of one such system: the social foraging of the ant Temnothorax rugatulus. Physically tiny with small population sizes, these cavity-dwelling ants provide a good model system to explore the mechanisms and ultimate origins of collective behavior in insect societies. My studies showed that colonies robustly exploit sugar water. Given a choice between feeders unequal in quality, colonies allocate more foragers to the better feeder. If the feeders change in quality, colonies are able to reallocate their foragers to the new location of the better feeder. These qualities of flexibility and allocation could be explained by the nature of positive feedback (tandem run recruitment) that these ants use. By observing foraging colonies with paint-marked ants, I was able to determine the `rules' that individuals follow: foragers recruit more and give up less when they find a better food source. By altering the nutritional condition of colonies, I found that these rules are flexible - attuned to the colony state. In starved colonies, individual ants are more likely to explore and recruit to food sources than in well-fed colonies. Similar to honeybees, Temmnothorax foragers appear to modulate their exploitation and recruitment behavior in response to environmental and social cues. Finally, I explored the influence of ecology (resource distribution) on the foraging success of colonies. Larger colonies showed increased consistency and a greater rate of harvest than smaller colonies, but this advantage was mediated by the distribution of resources. While patchy or rare food sources exaggerated the relative success of large colonies, regularly (or easily found) distributions leveled the playing field for smaller colonies. Social foraging in ant societies can best be understood when we view the colony as a single organism and the phenotype - group size, communication, and individual behavior - as integrated components of a homeostatic unit.Dissertation/ThesisPh.D. Biology 201

Organisation of foraging in ants

In social insects, foraging is often cooperative, and so requires considerable organisation. In most ants, organisation is a bottom-up process where decisions taken by individuals result in emergent colony level patterns. Individuals base their decisions on their internal state, their past experience, and their environment. By depositing trail pheromones, for example, ants can alter the environment, and thus affect the behaviour of their nestmates. The development of emergent patterns depends on both how individuals affect the environment, and how they react to changes in the environment. Chapters 4 – 9 investigate the role of trail pheromones and route memory in the ant Lasius niger. Route memories can form rapidly and be followed accurately, and when route memories and trail pheromones contradict each other, ants overwhelmingly follow route memories (chapter 4). Route memories and trail pheromones can also interact synergistically, allowing ants to forage faster without sacrificing accuracy (chapter 5). Home range markings also interact with other information sources to affect ant behaviour (chapter 6). Trail pheromones assist experienced ants when facing complex, difficult-to-learn routes (chapter 7). When facing complicated routes, ants deposit more pheromone to assist in navigation and learning (chapter 7). Deposition of trail pheromones is suppressed by ants leaving a marked path (chapter 5), strong pheromone trails (chapter 7) and trail crowding (chapter 8). Colony level ‘decisions’ can be driven by factors other than trail pheromones, such as overcrowding at a food source (chapter 9). Chapter 10 reviews the many roles of trail pheromones in ants. Chapters 11 – 14 focus on the organisation of cooperative food retrieval. Pheidole oxyops workers arrange themselves non-randomly around items to increase transport speeds (chapter 11). Groups of ants will rotate food items to reduce drag (chapter 12). Chapters 13 and 14 encompass the ecology of cooperative transport, and how it has shaped trail pheromone recruitment in P. oxyops and Paratrechina longicornis. Lastly, chapter 15 provide a comprehensive review of cooperative transport in ants and elsewhere

Ants in a Labyrinth: A Statistical Mechanics Approach to the Division of Labour

Division of labour (DoL) is a fundamental organisational principle in human societies, within virtual and robotic swarms and at all levels of biological organisation. DoL reaches a pinnacle in the insect societies where the most widely used model is based on variation in response thresholds among individuals, and the assumption that individuals and stimuli are well-mixed. Here, we present a spatially explicit model of DoL. Our model is inspired by Pierre de Gennes' 'Ant in a Labyrinth' which laid the foundations of an entire new field in statistical mechanics. We demonstrate the emergence, even in a simplified one-dimensional model, of a spatial patterning of individuals and a right-skewed activity distribution, both of which are characteristics of division of labour in animal societies. We then show using a two-dimensional model that the work done by an individual within an activity bout is a sigmoidal function of its response threshold. Furthermore, there is an inverse relationship between the overall stimulus level and the skewness of the activity distribution. Therefore, the difference in the amount of work done by two individuals with different thresholds increases as the overall stimulus level decreases. Indeed, spatial fluctuations of task stimuli are minimised at these low stimulus levels. Hence, the more unequally labour is divided amongst individuals, the greater the ability of the colony to maintain homeostasis. Finally, we show that the non-random spatial distribution of individuals within biological and social systems could be caused by indirect (stigmergic) interactions, rather than direct agent-to-agent interactions. Our model links the principle of DoL with principles in the statistical mechanics and provides testable hypotheses for future experiments

On the role of stigmergy in cognition

Cognition in animals is produced by the self- organized activity of mutually entrained body and brain. Given that stigmergy plays a major role in self-organization of societies, we identify stigmergic behavior in cognitive systems, as a common mechanism ranging from brain activity to social systems. We analyze natural societies and artificial systems exploiting stigmergy to produce cognition. Several authors have identified the importance of stigmergy in the behavior and cognition of social systems. However, the perspective of stigmergy playing a central role in brain activity is novel, to the best of our knowledge. We present several evidences of such processes in the brain and discuss their importance in the formation of cognition. With this we try to motivate further research on stigmergy as a relevant component for intelligent systems.info:eu-repo/semantics/acceptedVersio

Identifying cues for self-organized nest wall-building behaviour in the rock ant, Temnothorax rugatulus, using hidden Markov models

Funding: E.I.’s Ph.D. was funded by the John Templeton Foundation as part of the research collaboration grant ‘Putting the extended evolutionary synthesis to the test’ (grant no. 60501). The postdoctoral research project that followed this initial work was funded by an ASAB research grant to M.W. and E.I.European Temnothorax albipennis and its American counterpart Temnothorax rugatulus build circular walls to limit their nest area within a rock crevice. To determine wall position, workers are thought to rely on a distance template (from the cluster of brood and nurses at the nest centre) and on indirect social (i.e. stigmergic) information found in the aggregations of already-deposited building material. Analytical and simulation models of this behaviour predict that the combination of these two mechanisms can produce the observed wall structure, but there is so far no empirical evidence of either mechanism. Here, we find statistical evidence in support of the stigmergic relationship between stone density and deposition behaviour. We apply hidden Markov models (HMMs) to analyse wall-building data from four colonies of T. rugatulus. We show that material deposition activity changes following a parabolic relationship with the density of building material at building sites, different from the linear relationship hypothesized previously. This parabolic curve is similar to behavioural response curves identified in the nest enlargement process of several ant species. In addition, HMM analysis indicates the existence of two distinct states in T. rugatulus building activity. These states are associated with different mean building rates (that is, the two states can be described as a high and a low activity state) and might be caused by changes in task priorities during the colony process of settling into a new nest. This study updates one of the earliest models of self-organized animal behaviour.Peer reviewe

Social insects and swarm intelligence

Most of the questions on the dynamics of systems of strongly interacting (simple) agents we can pose could be reframed, without any modification, in the context of social insects, since these are, without any doubt, a truly paradigm for complex systems. This chapter surveys some of the mathematical models that have been successfully used to analyze swarm behavior.Postprint (published version

Active Inferants: An Active Inference Framework for Ant Colony Behavior

In this paper, we introduce an active inference model of ant colony foraging behavior, and implement the model in a series of in silico experiments. Active inference is a multiscale approach to behavioral modeling that is being applied across settings in theoretical biology and ethology. The ant colony is a classic case system in the function of distributed systems in terms of stigmergic decision-making and information sharing. Here we specify and simulate a Markov decision process (MDP) model for ant colony foraging. We investigate a well-known paradigm from laboratory ant colony behavioral experiments, the alternating T-maze paradigm, to illustrate the ability of the model to recover basic colony phenomena such as trail formation after food location discovery. We conclude by outlining how the active inference ant colony foraging behavioral model can be extended and situated within a nested multiscale framework and systems approaches to biology more generally