Noise improves collective decision-making by ants in dynamic environments

Spinodal decomposition and phase separation in polar active matter

We develop and study the hydrodynamic theory of flocking with autochemotaxis. This describes large collections of self-propelled entities all spontaneously moving in the same direction, each emitting a substance which attracts the others (e.g., ants). The theory combines features of the Keller-Segel model for autochemotaxis with the Toner-Tu theory of flocking. We find that sufficiently strong autochemotaxis leads to an instability of the uniformly moving state (the "flock"), in which bands of different density form moving parallel to the mean flock velocity with different speeds. This instability is, therefore, completely different from the well-known "banding instability," in which bands form perpendicular to the mean flock velocity. The bands we find, which are reminiscent of ant trails, coarsen over time to reach a phase-separated state, in which one high-density and one low-density band fill the entire system. The same instability, described by the same hydrodynamic theory, can occur in flocks phase separating due to any microscopic mechanism (e.g., sufficiently strong attractive interactions). Although in many ways analogous to equilibrium phase separation via spinodal decomposition, the two steady-state densities here are determined not by a common tangent construction, as in equilibrium, but by an uncommon tangent construction very similar to that found for motility-induced phase separation of disordered active particles. Our analytic theory agrees well with our numerical simulations of our equations of motion.

Ontogeny of collective behaviour

During their lifetime, superorganisms, like unitary organisms, undergo transformations that change the machinery of their collective behaviour. Here, we suggest that these transformations are largely understudied and propose that more systematic research into the ontogeny of collective behaviours is needed if we hope to better understand the link between proximate behavioural mechanisms and the development of collective adaptive functions. In particular, certain social insects engage in self-assemblage, forming dynamic and physically connected architectures with striking similarities to developing multicellular organisms, making them good model systems for ontogenetic studies of collective behaviour. However, exhaustive time series and three-dimensional data are required to thoroughly characterize the different life stages of the collective structures and the transitions between these stages. The well-established fields of embryology and developmental biology offer practical tools and theoretical frameworks that could speed up the acquisition of new knowledge about the formation, development, maturity and dissolution of social insect self-assemblages and, by extension, other superorganismal behaviours. We hope that this review will encourage an expansion of the ontogenetic perspective in the field of collective behaviour and, in particular, in self-assemblage research, which has far-reaching applications in robotics, computer science and regenerative medicine. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Alternative model systems for cognitive variation: eusocial-insect colonies

Understanding the origins and maintenance of cognitive variation in animal populations is central to the study of the evolution of cognition. However, the brain is itself a complex, hierarchical network of heterogeneous components, from diverse cell types to diverse neuropils, each of which may be of limited use to study in isolation or prohibitively challenging to manipulate in situ. Consequently, highly tractable alternative model systems may be valuable tools. Eusocial-insect colonies display emergent cognitive-like properties from relatively simple social interactions between diverse subunits that can be observed and manipulated while operating collectively. Here, we review the individual-scale mechanisms that cause group-level variation in how colonies solve problems analogous to cognitive challenges faced by brains, like decision-making, attention, and search.

Noise resistant synchronization and collective rhythm switching in a model of animal group locomotion

Biology is suffused with rhythmic behaviour, and interacting biological oscillators often synchronize their rhythms with one another. Colonies of some ant species are able to synchronize their activity to fall into coherent bursts, but models of this phenomenon have neglected the potential effects of intrinsic noise and interspecific differences in individual-level behaviour. We investigated the individual and collective activity patterns of two Leptothorax ant species. We show that in one species (Leptothorax sp. W), ants converge onto rhythmic cycles of synchronized collective activity with a period of about 20 min. A second species (Leptothorax crassipilis) exhibits more complex collective dynamics, where dominant collective cycle periods range from 16 min to 2.8 h. Recordings that last 35 h reveal that, in both species, the same colony can exhibit multiple oscillation frequencies. We observe that workers of both species can be stimulated by nest-mates to become active after a refractory resting period, but the durations of refractory periods differ between the species and can be highly variable. We model the emergence of synchronized rhythms using an agent-based model informed by our empirical data. This simple model successfully generates synchronized group oscillations despite the addition of noise to ants' refractory periods. We also find that adding noise reduces the likelihood that the model will spontaneously switch between distinct collective cycle frequencies.

Dynamics of task allocation in social insect colonies: scaling effects of colony size versus work activities

The mechanisms through which work is organized are central to understanding how complex systems function. Previous studies suggest that task organization can emerge via nonlinear dynamical processes wherein individuals interact and modify their behavior through simple rules. However, there is very limited theory about how those processes are shaped by behavioral variation within social groups. In this work, we propose an adaptive modeling framework on task allocation by incorporating variation both in task performance and task-related metabolic rates. We study the scaling effects of colony size on the resting probability as well as task allocation. We also numerically explore the effects of stochastic noise on task allocation in social insect colonies. Our theoretical and numerical results show that: (a) changes in colony size can regulate the probability of colony resting and the allocation of tasks, and the direction of regulation depends on the nonlinear metabolic scaling effects of tasks; (b) increased response thresholds may cause colonies to rest in varied patterns such as periodicity. In this case, we observed an interesting bubble phenomenon in the task allocation of social insect colonies for the first time; (c) stochastic noise can cause work activities and task demand to fluctuate within a range, where the amplitude of the fluctuation is positively correlated with the intensity of noise.

Quorum sensing via dynamic cytokine signaling comprehensively explains divergent patterns of effector choice among helper T cells

In the animal kingdom, various forms of swarming enable groups of autonomous individuals to transform uncertain information into unified decisions which are probabilistically beneficial. Crossing scales from individual to group decisions requires dynamically accumulating signals among individuals. In striking parallel, the mammalian immune system is also a group of decentralized autonomous units (i.e. cells) which collectively navigate uncertainty with the help of dynamically accumulating signals (i.e. cytokines). Therefore, we apply techniques of understanding swarm behavior to a decision-making problem in the mammalian immune system, namely effector choice among CD4+ T helper (Th) cells. We find that incorporating dynamic cytokine signaling into a simple model of Th differentiation comprehensively explains divergent observations of this process. The plasticity and heterogeneity of individual Th cells, the tunable mixtures of effector types that can be generated in vitro, and the polarized yet updateable group effector commitment often observed in vivo are all explained by the same set of underlying molecular rules. These rules reveal that Th cells harness dynamic cytokine signaling to implement a system of quorum sensing. Quorum sensing, in turn, may confer adaptive advantages on the mammalian immune system, especially during coinfection and during coevolution with manipulative parasites. This highlights a new way of understanding the mammalian immune system as a cellular swarm, and it underscores the power of collectives throughout nature.

Insights about collective decision-making at the genetic level

By living in a collective, individuals can share and aggregate information to base their decisions on the many rather than on the one, thereby increasing accuracy. But a collective can also be defined at the molecular level. In the following, we reason that genes, by working collectively, share fundamental features with social organisms, which ends, without invoking cognition, in wiser responses. For that, we compile into a single picture the terms redundancy, stochastic resonance, intrinsic and extrinsic noise, and cross-regulation.

Social inhibition maintains adaptivity and consensus of honeybees foraging in dynamic environments

To effectively forage in natural environments, organisms must adapt to changes in the quality and yield of food sources across multiple timescales. Individuals foraging in groups act based on both their private observations and the opinions of their neighbours. How do these information sources interact in changing environments? We address this problem in the context of honeybee colonies whose inhibitory social interactions promote adaptivity and consensus needed for effective foraging. Individual and social interactions within a mathematical model of collective decisions shape the nutrition yield of a group foraging from feeders with temporally switching quality. Social interactions improve foraging from a single feeder if temporal switching is fast or feeder quality is low. When the colony chooses from multiple feeders, the most beneficial form of social interaction is direct switching, whereby bees flip the opinion of nest-mates foraging at lower-yielding feeders. Model linearization shows that effective social interactions increase the fraction of the colony at the correct feeder (consensus) and the rate at which bees reach that feeder (adaptivity). Our mathematical framework allows us to compare a suite of social inhibition mechanisms, suggesting experimental protocols for revealing effective colony foraging strategies in dynamic environments.

Changing of the guard: mixed specialization and flexibility in nest defense (Tetragonisca angustula)

Task allocation is a central challenge of collective behavior in a variety of group-living species, and this is particularly the case for the allocation of social insect workers for group defense. In social insects, both benefits and considerable costs are associated with the production of specialized soldiers. We asked whether colonies mitigate costs of production of specialized soldiers by simultaneously employing behavioral flexibility in nonspecialist workers that can augment defense capabilities at short time scales. We studied colonies of the stingless bee Tetragonisca angustula, a species that has 2 discrete nest-guarding tasks typically performed by majors: hovering guarding and standing guarding. Majors showed age polyethism across nest-guarding tasks, first hovering and then changing to the task of standing guarding after 1 week. Colonies were also able to reassign minors to guarding tasks when majors were experimentally removed. Replacement guards persisted in nest defense tasks until colonies produced enough majors to return to their initial state. Tetragonisca angustula colonies thus employed a coordinated set of specialization strategies in nest defense: morphologically specialized soldiers, age polyethism among soldiers within specific guarding tasks, and rapid flexible reallocation of nonspecialists to guarding during soldier loss. This mixed strategy achieves the benefits of a highly specialized defensive force while maintaining the potential for rapid reinforcement when soldiers are lost or colonies face unexpectedly intense attack.

Same length, different shapes: ants collectively choose a straight foraging path over a bent one

In socials insects, exploration is fundamental for the discovery of food resources and determines decision-making. We investigated how the interplay between the physical characteristics of the paths leading to food sources and the way it impacts the behaviour of individual ants affects their collective decisions. Colonies of different sizes of Lasius niger had access to two equal food sources through two paths of equal length but of different geometries: one was straight between the nest and the food source, and the other involved an abrupt change of direction at the midway point (135°). Both food sources were discovered simultaneously, but the food source at the end of the straight path was preferentially exploited by ants. Based on experimental and theoretical results, we show that a significantly shorter duration of nestbound travel on the straight path, which rapidly leads to a stronger pheromone trail, is at the origin of this preference.

Ants Use Multiple Spatial Memories and Chemical Pointers to Navigate Their Nest

Animal navigation relies on the available environmental cues and, where present, visual cues typically dominate. While much is known about vision-assisted navigation, knowledge of navigation in the dark is scarce. Here, we combine individual tracking, dynamic modular nest structures, and spatially resolved chemical profiling to study how Camponotus fellah ants navigate within the dark labyrinth of their nest. We find that, contrary to ant navigation above ground, underground navigation cannot rely on long-range information. This limitation emphasizes the ants' capabilities associated with other navigational strategies. Indeed, apart from gravity, underground navigation relies on self-referenced memories of multiple locations and on socially generated chemical cues placed at decision points away from the target. Moreover, the ants quickly readjust the weights attributed to these information sources in response to environmental changes. Generally, studying well-known behaviors in a variety of environmental contexts holds the potential of revealing new insights into animal cognition.

•

We combine multiple technologies to study how ants navigate within their dark nest

•

Ants substitute visual cues with gravity, chemical cues, and multi-target memories

•

Following a catastrophe, ants quickly readjust the relative importance of cues

Diverse stochasticity leads a colony of ants to optimal foraging

A mathematical model of garden ants (Lasius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pheromone trails and the group foraging efficiency. Numerical simulations of the model indicate that depending on the systematic change of the feeding environment, the optimal distribution of stochasticity shifts from a mixture of almost deterministic and mildly stochastic ants to a contrasted mixture of almost deterministic ants and highly stochastic ants. In addition, the interaction between the stochasticity and the pheromone path regulates the dynamics of the foraging efficiency optimization. Stochasticity could strengthen the collective efficiency when the variance in the sensitivity to pheromone for ants is introduced in the model.

Regulatory mechanism predates the evolution of self-organizing capacity in simulated ant-like robots

The evolution of complexity is one of the prime features of life on Earth. Although well accepted as the product of adaptation, the dynamics underlying the evolutionary build-up of complex adaptive systems remains poorly resolved. Using simulated robot swarms that exhibit ant-like group foraging with trail pheromones, we show that their self-organizing capacity paradoxically involves regulatory behavior that arises in advance. We focus on a traffic rule on their foraging trail as a regulatory trait. We allow the simulated robot swarms to evolve pheromone responsiveness and traffic rules simultaneously. In most cases, the traffic rule, initially arising as selectively neutral component behaviors, assists the group foraging system to bypass a fitness valley caused by overcrowding on the trail. Our study reveals a hitherto underappreciated role of regulatory mechanisms in the origin of complex adaptive systems, as well as highlights the importance of embodiment in the study of their evolution.

Instructed subsets or agile swarms: how T-helper cells may adaptively counter uncertainty with variability and plasticity

Over recent years, extensive phenotypic variability and plasticity have been revealed among the T-helper cells of the mammalian adaptive immune system, even within clonal lineages of identical antigen specificity. This challenges the conventional view that T-helper cells assort into functionally distinct subsets following differential instruction by the innate immune system. We argue that the adaptive value of coping with uncertainty can reconcile the 'instructed subset' framework with T-helper variability and plasticity. However, we also suggest that T-helper cells might better be understood as agile swarms engaged in collective decision-making to promote host fitness. With rigorous testing, the 'agile swarms' framework may illuminate how variable and plastic individual T-helper cells interact to create coherent immunity.

Effect of the land area elevation on the collective choice in ants

Collective decisions regarding food source exploitation in social insects are influenced by a range of parameters, from source quality to individual preference and social information sharing. Those regarding the elevation of the physical trail towards a food source have been neglected. In this work, we investigated the effect of ascending and descending paths from the nest to a food source on collective choice in two ant species Lasius niger and Myrmica rubra. Our hypothesis that returning loaded with food from the high source is more energy efficient was validated by choice experiments: when the sources are simultaneously introduced the high food source is preferentially exploited by both species. The flexibility of colony response was then tested by introducing the preferred source (high) incidentally, after recruitment towards the down food source began. Despite the well-known lack of flexibility of L. niger, both species showed the ability to reallocate their foraging workforce towards the highest food source. The collective choice and the flexibility are based on the difference between the u-turn rates when foragers are facing the ascending or descending branch. We discuss these results in terms of species-specifics characteristics and ecological context.

Mandevillian intelligence

Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices (i.e., shortcomings, limitations, constraints and biases) are seen to play a positive functional role in yielding collective forms of cognitive success. The present paper introduces the concept of mandevillian intelligence and reviews a number of strands of empirical research that help to shed light on the phenomenon. The paper also attempts to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch as we accept the notion of mandevillian intelligence, then it seems that the cognitive and epistemic value of a specific social or technological intervention will vary according to whether our attention is focused at the individual or collective level of analysis. This has a number of important implications for how we think about the design and evaluation of collective cognitive systems. For example, the notion of mandevillian intelligence forces us to take seriously the idea that the exploitation (or even the accentuation) of individual cognitive shortcomings could, in some situations, provide a productive route to collective forms of cognitive and epistemic success.

The role of noise in self-organized decision making by the true slime mold Physarum polycephalum

Self-organized mechanisms are frequently encountered in nature and known to achieve flexible, adaptive control and decision-making. Noise plays a crucial role in such systems: It can enable a self-organized system to reliably adapt to short-term changes in the environment while maintaining a generally stable behavior. This is fundamental in biological systems because they must strike a delicate balance between stable and flexible behavior. In the present paper we analyse the role of noise in the decision-making of the true slime mold Physarum polycephalum, an important model species for the investigation of computational abilities in simple organisms. We propose a simple biological experiment to investigate the reaction of P. polycephalum to time-variant risk factors and present a stochastic extension of an established mathematical model for P. polycephalum to analyze this experiment. It predicts that-due to the mechanism of stochastic resonance-noise can enable P. polycephalum to correctly assess time-variant risk factors, while the corresponding noise-free system fails to do so. Beyond the study of P. polycephalum we demonstrate that the influence of noise on self-organized decision-making is not tied to a specific organism. Rather it is a general property of the underlying process dynamics, which appears to be universal across a wide range of systems. Our study thus provides further evidence that stochastic resonance is a fundamental component of the decision-making in self-organized macroscopic and microscopic groups and organisms.

Ant workers exhibit specialization and memory during raft formation

By working together, social insects achieve tasks that are beyond the reach of single individuals. A striking example of collective behaviour is self-assembly, a process in which individuals link their bodies together to form structures such as chains, ladders, walls or rafts. To get insight into how individual behavioural variation affects the formation of self-assemblages, we investigated the presence of task specialization and the role of past experience in the construction of ant rafts. We subjected groups of Formica selysi workers to two consecutive floods and monitored the position of individuals in rafts. Workers showed specialization in their positions when rafting, with the same individuals consistently occupying the top, middle, base or side position in the raft. The presence of brood modified workers' position and raft shape. Surprisingly, workers' experience in the first rafting trial with brood influenced their behaviour and raft shape in the subsequent trial without brood. Overall, this study sheds light on the importance of workers' specialization and memory in the formation of self-assemblages.

Private information alone can trigger trapping of ant colonies in local feeding optima

Ant colonies are famous for using trail pheromones to make collective decisions. Trail pheromone systems are characterised by positive feedback, which results in rapid decision making. However, in an iconic experiment ants were shown to become ‘trapped’ in exploiting a poor food source, if it was discovered earlier. This has conventionally been explained by the established pheromone trail becoming too strong for new trails to compete. However, many social insects have a well-developed memory, and private information often overrules conflicting social information. Thus, route memory could also explain this collective ‘trapping’ effect. Here we disentangle the effects of social and private information in two ‘trapping’ experiments; one in which ants are presented a good and poor food source, and one in which ants are presented a long and short path to the same food source. We find that private information is sufficient to trigger trapping in selecting the poorer of two food sources, and may be sufficient to cause it altogether. Memories did not trigger trapping in the shortest path experiment, likely as sufficiently detailed memories did not form. The fact that collective decisions can be triggered by private information alone may require other collective patterns previously attributed solely to social information use to be reconsidered.

Trail pheromones: an integrative view of their role in social insect colony organization

Trail pheromones do more than simply guide social insect workers from point A to point B. Recent research has revealed additional ways in which they help to regulate colony foraging, often via positive and negative feedback processes that influence the exploitation of the different resources that a colony has knowledge of. Trail pheromones are often complementary or synergistic with other information sources, such as individual memory. Pheromone trails can be composed of two or more pheromones with different functions, and information may be embedded in the trail network geometry. These findings indicate remarkable sophistication in how trail pheromones are used to regulate colony-level behavior, and how trail pheromones are used and deployed at the individual level.

How to not get stuck-negative feedback due to crowding maintains flexibility in ant foraging

Ant foraging is an important model system in the study of adaptive complex systems. Many ants use trail pheromones to recruit nestmates to resources. Differential recruitment depending on resource quality coupled with positive feedback allows ant colonies to make rapid and accurate collective decisions about how best to allocate their work-force. However, ant colonies can become trapped in sub-optimal foraging decisions if recruitment to a poor resource becomes too strong before a better resource is discovered. Genetic algorithms and Ant Colony Optimisation heuristics can also suffer from being trapped in such local optima. Recently, two negative feedback effects were described, in which an increase in crowding (crowding negative feedback-CNF) or trail pheromones (pheromone negative feedback-PNF) caused a decrease in subsequent pheromone deposition. Using agent based simulations with realistic parameters I test whether these negative feedback effects can prevent simulated ant colonies from becoming trapped in sub-optimal foraging decisions. Colonies are presented with two food sources of different qualities, and these qualities switch part way through the experiment. When either no negative feedback effects are implemented or only PNF is implemented colonies are completely unable to refocus their foraging effort to the high quality feeder. However, when CNF alone is implemented at a realistic level 97% of colonies successfully refocus their foraging effort. This ability to refocus colony foraging efforts is due to the strong reduction of pheromone deposition caused by CNF. This suggests that CNF is an important behaviour enabling ant colonies to maintain foraging flexibility. However, CNF comes at a slight cost to colonies when making their initial foraging decision.

Error in the honeybee waggle dance improves foraging flexibility

The honeybee waggle dance communicates the location of profitable food sources, usually with a certain degree of error in the directional information ranging from 10–15° at the lower margin. We simulated one-day colonial foraging to address the biological significance of information error in the waggle dance. When the error was 30° or larger, the waggle dance was not beneficial. If the error was 15°, the waggle dance was beneficial when the food sources were scarce. When the error was 10° or smaller, the waggle dance was beneficial under all the conditions tested. Our simulation also showed that precise information (0–5° error) yielded great success in finding feeders, but also caused failures at finding new feeders, i.e., a high-risk high-return strategy. The observation that actual bees perform the waggle dance with an error of 10–15° might reflect, at least in part, the maintenance of a successful yet risky foraging trade-off.

Negative feedback enables fast and flexible collective decision-making in ants

Positive feedback plays a major role in the emergence of many collective animal behaviours. In many ants pheromone trails recruit and direct nestmate foragers to food sources. The strong positive feedback caused by trail pheromones allows fast collective responses but can compromise flexibility. Previous laboratory experiments have shown that when the environment changes, colonies are often unable to reallocate their foragers to a more rewarding food source. Here we show both experimentally, using colonies of Lasius niger, and with an agent-based simulation model, that negative feedback caused by crowding at feeding sites allows ant colonies to maintain foraging flexibility even with strong recruitment to food sources. In a constant environment, negative feedback prevents the frequently found bias towards one feeder (symmetry breaking) and leads to equal distribution of foragers. In a changing environment, negative feedback allows a colony to quickly reallocate the majority of its foragers to a superior food patch that becomes available when foraging at an inferior patch is already well underway. The model confirms these experimental findings and shows that the ability of colonies to switch to a superior food source does not require the decay of trail pheromones. Our results help to resolve inconsistencies between collective foraging patterns seen in laboratory studies and observations in the wild, and show that the simultaneous action of negative and positive feedback is important for efficient foraging in mass-recruiting insect colonies.

Key factors for the emergence of collective decision in invertebrates

In many species of group living invertebrates, in particular arthropods, collective decisions can emerge from the combined actions of individuals and the direct or indirect interactions between individuals. These decisions allow groups of individuals to respond quickly and accurately to changes that occur in their environment. Examples of such decisions are found in a variety of invertebrate taxa and in many different contexts, e.g., exploring a new territory, foraging for food, finding a suitable location where to aggregate or to establish a nest, defending oneself against predators, etc. In this paper we review the collective decisions that have been documented in different invertebrate taxa where individuals are known to live temporarily or permanently in social or gregarious groups. We first present some simple examples of collective decisions involving the choice between two alternatives. We then define the fundamental rules required for these collective decisions to emerge throughout the invertebrate taxon, from simple organisms such as caterpillars, to animals endowed with highly developed perceptive and cognitive capacities such as ants and bees. The presentation of these rules gives us the opportunity to illustrate one of the pitfalls of the study of collective choice in animals by showing through computer simulations how a choice between two alternatives can be misinterpreted as the result of the action of self-organized mechanisms. In the second part, we discuss the peculiarities of collective decisions in invertebrates, their properties, and characteristics. We conclude by discussing the issue of individual complexity in collective decision-making process.

Working against gravity: horizontal honeybee waggle runs have greater angular scatter than vertical waggle runs

The presence of noise in a communication system may be adaptive or may reflect unavoidable constraints. One communication system where these alternatives are debated is the honeybee (Apis mellifera) waggle dance. Successful foragers communicate resource locations to nest-mates by a dance comprising repeated units (waggle runs), which repetitively transmit the same distance and direction vector from the nest. Intra-dance waggle run variation occurs and has been hypothesized as a colony-level adaptation to direct recruits over an area rather than a single location. Alternatively, variation may simply be due to constraints on bees' abilities to orient waggle runs. Here, we ask whether the angle at which the bee dances on vertical comb influences waggle run variation. In particular, we determine whether horizontal dances, where gravity is not aligned with the waggle run orientation, are more variable in their directional component. We analysed 198 dances from foragers visiting natural resources and found support for our prediction. More horizontal dances have greater angular variation than dances performed close to vertical. However, there is no effect of waggle run angle on variation in the duration of waggle runs, which communicates distance. Our results weaken the hypothesis that variation is adaptive and provide novel support for the constraint hypothesis.

Intra-dance variation among waggle runs and the design of efficient protocols for honey bee dance decoding

Noise is universal in information transfer. In animal communication, this presents a challenge not only for intended signal receivers, but also to biologists studying the system. In honey bees, a forager communicates to nestmates the location of an important resource via the waggle dance. This vibrational signal is composed of repeating units (waggle runs) that are then averaged by nestmates to derive a single vector. Manual dance decoding is a powerful tool for studying bee foraging ecology, although the process is time-consuming: a forager may repeat the waggle run 1- >100 times within a dance. It is impractical to decode all of these to obtain the vector; however, intra-dance waggle runs vary, so it is important to decode enough to obtain a good average. Here we examine the variation among waggle runs made by foraging bees to devise a method of dance decoding. The first and last waggle runs within a dance are significantly more variable than the middle run. There was no trend in variation for the middle waggle runs. We recommend that any four consecutive waggle runs, not including the first and last runs, may be decoded, and we show that this methodology is suitable by demonstrating the goodness-of-fit between the decoded vectors from our subsamples with the vectors from the entire dances.

Just follow your nose: homing by olfactory cues in ants

How is an ant-equipped with a brain that barely exceeds the size of a pinhead-capable of achieving navigational marvels? Even though evidences suggest that navigation is a multimodal process, ants heavily depend on olfactory cues-of pheromonal and non-pheromonal nature-for foraging and orientation. Recent studies have directed their attention to the efficiency of pheromone trail networks. Advances in neurophysiological techniques make it possible to investigate trail pheromone processing in the ant's brain. In addition to relying on pheromone odours, ants also make use of volatiles emanating from the nest surroundings. Deposited in the vicinity of the nest, these home-range markings help the ants to home after a foraging run. Furthermore, olfactory landmarks associated with the nest enhance ants' homing abilities.

Optimisation in a natural system: Argentine ants solve the Towers of Hanoi

Natural systems are a source of inspiration for computer algorithms designed to solve optimisation problems. Yet most 'nature-inspired' algorithms take only superficial inspiration from biology, and little is known about how real biological systems solve difficult problems. Moreover, ant algorithms, neural networks and similar methods are usually applied to static problems, whereas most biological systems have evolved to perform under dynamically changing conditions. We used the Towers of Hanoi puzzle to test whether Argentine ants can solve a potentially difficult optimisation problem. We also tested whether the ants can adapt to dynamic changes in the problem. We mapped all possible solutions to the Towers of Hanoi on a single graph and converted this into a maze for the ants to solve. We show that the ants are capable of solving the Towers of Hanoi, and are able to adapt when sections of the maze are blocked off and new sections installed. The presence of exploration pheromone increased the efficiency of the resulting network and increased the ants' ability to adapt to changing conditions. Contrary to previous studies, our study shows that mass-recruiting ant species such as the Argentine ant can forage effectively in a dynamic environment. Our results also suggest that novel optimisation algorithms can benefit from stronger biological mimicry.