Low-distortion information propagation with noise suppression in swarm networks.

A method for low-distortion (low-dissipation, low-dispersion) information propagation in swarm-type networks with suppression of high-frequency noise is presented. Information propagation in current neighbor-based networks, where each agent seeks to achieve a consensus with its neighbors, is diffusion-like, dissipative, and dispersive and does not reflect the wave-like (superfluidic) behavior seen in nature. However, pure wave-like neighbor-based networks have two challenges: i) It requires additional communication for sharing information about time derivatives and ii) it can lead to information decoherence through noise at high frequencies. The main contribution of this work is to show that delayed self-reinforcement (DSR) by the agents using prior information (e.g., using short-term memory) can lead to the wave-like information propagation at low-frequencies as seen in nature without the need for additional information sharing between the agents. Moreover, it is shown that the DSR can be designed to enable suppression of high-frequency noise transmission while limiting the dissipation and dispersion of (lower-frequency) information content leading to similar (cohesive) behavior of agents. In addition to explaining noise-suppressed wave-like information transfer in natural systems, the result impacts the design of noise-suppressing cohesive algorithms for engineered networks.

Flock2: A model for orientation-based social flocking.

The aerial flocking of birds, or murmurations, has fascinated observers while presenting many challenges to behavioral study and simulation. We examine how the periphery of murmurations remain well bounded and cohesive. We also investigate agitation waves, which occur when a flock is disturbed, developing a plausible model for how they might emerge spontaneously. To understand these behaviors a new model is presented for orientation-based social flocking. Previous methods model inter-bird dynamics by considering the neighborhood around each bird, and introducing forces for avoidance, alignment, and cohesion as three dimensional vectors that alter acceleration. Our method introduces orientation-based social flocking that treats social influences from neighbors more realistically as a desire to turn, indirectly controlling the heading in an aerodynamic model. While our model can be applied to any flocking social bird we simulate flocks of starlings, Sturnus vulgaris, and demonstrate the possibility of orientation waves in the absence of predators. Our model exhibits spherical and ovoidal flock shapes matching observation. Comparisons of our model to Reynolds' on energy consumption and frequency analysis demonstrates more realistic motions, significantly less energy use in turning, and a plausible mechanism for emergent orientation waves.

Interaction Rules Supporting Effective Flocking Behavior.

Several simulation models have demonstrated how flocking behavior emerges from the interaction among individuals that react to the relative orientation of their neighbors based on simple rules. However, the precise nature of these rules and the relationship between the characteristics of the rules and the efficacy of the resulting collective behavior are unknown. In this article, we analyze the effect of the strength with which individuals react to the orientation of neighbors located in different sectors of their visual fields and the benefit that could be obtained by using control rules that are more elaborate than those normally used. Our results demonstrate that considering only neighbors located on the frontal side of the visual field permits an increase in the aggregation level of the swarm. Using more complex rules and/or additional sensory information does not lead to better performance.

The effect of sociality on competitive interactions among birds.

Sociality can provide many benefits, including increased foraging success, reproductive opportunities and defence against predation. How does sociality influence the dominance hierarchies of ecological competitors? Here, we address this question using a large citizen science dataset of competitive interactions among birds foraging at backyard feeders, representing a network of over 55 000 interactions among 68 common species. We first show that species differ in average group size (the number of conspecifics observed together) as a fundamental measure of sociality. When analysing heterospecific competition, we find that sociality is inversely related to dominance. On average, a single individual from a solitary species is more likely to displace a size-matched opponent than a single individual from a social species. Yet, we find that social species gain an increase in their competitive advantage when in the presence of their conspecifics, which may occur as a result of dynamics within their groups. Finally, we show that more social species have relatively fewer dominance interactions with heterospecifics, and more with conspecifics. Overall, these results demonstrate that sociality can influence competition in ecological networks. More social species have decreased competitive ability as individuals, but they may gain competitive ability in groups.

Distinct patterns of gene expression in the medial preoptic area are related to gregarious singing behavior in European starlings (Sturnus vulgaris).

BACKGROUND: Song performed in flocks by European starlings (Sturnus vulgaris), referred to here as gregarious song, is a non-sexual, social behavior performed by adult birds. Gregarious song is thought to be an intrinsically reinforced behavior facilitated by a low-stress, positive affective state that increases social cohesion within a flock. The medial preoptic area (mPOA) is a region known to have a role in the production of gregarious song. However, the neurochemical systems that potentially act within this region to regulate song remain largely unexplored. In this study, we used RNA sequencing to characterize patterns of gene expression in the mPOA of male and female starlings singing gregarious song to identify possibly novel neurotransmitter, neuromodulator, and hormonal pathways that may be involved in the production of gregarious song. RESULTS: Differential gene expression analysis and rank rank hypergeometric analysis indicated that dopaminergic, cholinergic, and GABAergic systems were associated with the production of gregarious song, with multiple receptor genes (e.g., DRD2, DRD5, CHRM4, GABRD) upregulated in the mPOA of starlings who sang at high rates. Additionally, co-expression network analyses identified co-expressing gene clusters of glutamate signaling-related genes associated with song. One of these clusters contained five glutamate receptor genes and two glutamate scaffolding genes and was significantly enriched for genetic pathways involved in neurodevelopmental disorders associated with social deficits in humans. Two of these genes, GRIN1 and SHANK2, were positively correlated with performance of gregarious song. CONCLUSIONS: This work provides new insights into the role of the mPOA in non-sexual, gregarious song in starlings and highlights candidate genes that may play a role in gregarious social interactions across vertebrates. The provided data will also allow other researchers to compare across species to identify conserved systems that regulate social behavior.

Stochasticity may generate coherent motion in bird flocks.

Murmurations along with other forms of flocking have come to epitomize collective animal movements. Most studies into these stunning aerial displays have aimed to understand how coherent motion may emerge from simple behavioral rules and behavioral correlations. These studies may now need revision because recently it has been shown that flocking birds, like swarming insects, behave on the average as if they are trapped in elastic potential wells. Here I show, somewhat paradoxically, how coherent motion can be generated by variations in the intensity of multiplicative noise which causes the shape of a potential well to change, thereby shifting the positions and strengths of centres of attraction. Each bird, irrespective of its position in the flock will respond in a similar way to such changes, giving the impression that the flock behaves as one, and typically resulting in scale-free correlations. I thereby show how correlations can be an emergent property of noisy, confining potential wells. I also show how such wells can lead to high density borders, a characteristic of flocks, and I show how they can account for the complex patterns of collective escape patterns of starling flocks under predation. I suggest swarming and flocking do not constitute two distinctly different kinds of collective behavior but rather that insects are residing in relatively stable potential wells whilst birds are residing in unstable potential wells. It is shown how, dependent upon individual perceptual capabilities, bird flocks can be poised at criticality.

Collective response to local perturbations: how to evade threats without losing coherence.

Living groups move in complex environments and are constantly subject to external stimuli, predatory attacks and disturbances. An efficient response to such perturbations is vital to maintain the group's coherence and cohesion. Perturbations are often local, i.e. they are initially perceived only by few individuals in the group, but can elicit a global response. This is the case of starling flocks, that can turn very quickly to evade predators. In this paper, we investigate the conditions under which a global change of direction can occur upon local perturbations. Using minimal models of self-propelled particles, we show that a collective directional response occurs on timescales that grow with the system size and it is, therefore, a finite-size effect. The larger the group is, the longer it will take to turn. We also show that global coherent turns can only take place if i) the mechanism for information propagation is efficient enough to transmit the local reaction undamped through the whole group; and if ii) motility is not too strong, to avoid that the perturbed individual leaves the group before the turn is complete. No compliance with such conditions results in the group's fragmentation or in a non-efficient response.

Flock size increases with the diversity and abundance of local predators in an avian family.

Group living has long been viewed as an adaptation to reduce predation risk. Earlier comparative analyses provided support for the hypothesis but typically ignored variation in group size at the local scale and included proxies of predation risk rather than more direct estimates. Here, we related variation in group size at the scale of a study site in various species with the diversity and abundance of local predators. If larger groups provide protection against predators, we expected larger groups to evolve in species facing locally more diverse and abundant predators. We examined this hypothesis in one avian family, the Paridae, which are small arboreal birds that include some of the better studied species in ecology. From the literature, we gathered 275 flock size estimates from 34 species. In a phylogenetic framework and controlling for the potential confounding effect of latitude, we found that flock size increased with predation risk but only in flocks that included more than one species. We suggest that competition sets an upper limit to the size of flocks including conspecifics only. Joining flocks with other species, thus, allows individuals to increase flock size in response to higher predation risk without a substantial increase in competition. Overall, our results based on more direct estimates of predation risk provide further comparative evidence for an association between predation and the evolution of flocking in birds.

Leader-Based Flocking of Multiple Swarm Robots in Underwater Environments.

Considering underwater environments, this paper tackles flocking of multiple swarm robots utilizing one leader. The mission of swarm robots is to reach their goal while not colliding with a priori unknown 3D obstacles. In addition, the communication link among the robots needs to be preserved during the maneuver. Only the leader has sensors for localizing itself while accessing the global goal position. Every robot, except for the leader, can measure the relative position and the ID of its neighboring robots by utilizing proximity sensors such as Ultra-Short BaseLine acoustic positioning (USBL) sensors. Under the proposed flocking controls, multiple robots flock inside a 3D virtual sphere while preserving communication connectivity with the leader. If necessary, all robots rendezvous at the leader to increase connectivity among the robots. The leader herds all robots to reach the goal safely, while the network connectivity is maintained in cluttered underwater environments. To the best of our knowledge, our article is novel in developing underwater flocking controls utilizing one leader, so that a swarm of robots can safely flock to the goal in a priori unknown cluttered environments. MATLAB simulations were utilized to validate the proposed flocking controls in underwater environments with many obstacles.

Arbitrage Equilibrium, Invariance, and the Emergence of Spontaneous Order in the Dynamics of Bird-like Agents.

The physics of active biological matter, such as bacterial colonies and bird flocks, exhibiting interesting self-organizing dynamical behavior has gained considerable importance in recent years. Current theoretical advances use techniques from hydrodynamics, kinetic theory, and non-equilibrium statistical physics. However, for biological agents, these approaches do not seem to recognize explicitly their critical feature: namely, the role of survival-driven purpose and the attendant pursuit of maximum utility. Here, we propose a game-theoretic framework, statistical teleodynamics, that demonstrates that the bird-like agents self-organize dynamically into flocks to approach a stable arbitrage equilibriumof equal effective utilities. This is essentially the invisible handmechanism of Adam Smith's in an ecological context. What we demonstrate is for ideal systems, similar to the ideal gas or Ising model in thermodynamics. The next steps would involve examining and learning how real swarms behave compared to their ideal versions. Our theory is not limited to just birds flocking but can be adapted for the self-organizing dynamics of other active matter systems.

Formation and Flocking Control Algorithms for Robot Networks with Double Integrator Dynamics and Time-Varying Formations.

In this work, we study the problem of designing control laws that achieve time-varying formation and flocking behaviors in robot networks where each agent or robot presents double integrator dynamics. To design the control laws, we adopt a hierarchical control approach. First, we introduce a virtual velocity, which is used as a virtual control input for the position subsystem (outer loop). The objective of the virtual velocity is to achieve collective behaviors. Then, we design a velocity tracking control law for the velocity subsystem (inner loop). An advantage of the proposed approach is that the robots do not require the velocity of their neighbors. Additionally, we address the case in which the second state of the system is not available for feedback. We include a set of simulation results to show the performance of the proposed control laws.

Optimum k-Nearest Neighbors for Heading Synchronization on a Swarm of UAVs under a Time-Evolving Communication Network.

Heading synchronization is fundamental in flocking behaviors. If a swarm of unmanned aerial vehicles (UAVs) can exhibit this behavior, the group can establish a common navigation route. Inspired by flocks in nature, the k-nearest neighbors algorithm modifies the behavior of a group member based on the k closest teammates. This algorithm produces a time-evolving communication network, due to the continuous displacement of the drones. Nevertheless, this is a computationally expensive algorithm, especially for large groups. This paper contains a statistical analysis to determine an optimal neighborhood size for a swarm of up to 100 UAVs, that seeks heading synchronization using a simple P-like control algorithm, in order to reduce the calculations on every UAV, this is especially important if it is intended to be implemented in drones with limited capabilities, as in swarm robotics. Based on the literature of bird flocks, that establishes that the neighborhood of every bird is fixed around seven teammates, two approaches are treated in this work: (i) the analysis of the optimum percentage of neighbors from a 100-UAV swarm, that is necessary to achieve heading synchronization, and (ii) the analysis to determine if the problem is solved in swarms of different sizes, up to 100 UAVs, while maintaining seven nearest neighbors among the members of the group. Simulation results and a statistical analysis, support the idea that the simple control algorithm behaves like a flock of starlings.

Flocking Behaviors under Hierarchical Leadership of Thermodynamic Cucker-Smale Particles with Multiplicative White Noise and Perturbation.

The thermodynamic Cucker-Smale model (TCS model) describes dynamic consistency caused by different temperatures between multi-agent particles. This paper studies the flocking behaviors of the TCS model with multiplicative white noise under hierarchical leadership. First, we introduce the corresponding model of two particles. Then, by using mathematical induction and considering the properties of differential functions, it is proved that, under certain conditions, the group can achieve flocking. Finally, we verify the conclusion through numerical simulation results. Similarly, this paper studies the above model with perturbation functions.

Collective movement as a solution to noisy navigation and its vulnerability to population loss.

Many animals use the geomagnetic field to migrate long distances with high accuracy; however, research has shown that individual responses to magnetic cues can be highly variable. Thus, it has been hypothesized that magnetoreception alone is insufficient for accurate migrations and animals must either switch to a more accurate sensory cue or integrate their magnetic sense over time. Here we suggest that magnetoreceptive migrators could also use collective navigation strategies. Using agent-based models, we compare agents utilizing collective navigation to both the use of a secondary sensory system and time-integration. Our models demonstrate that collective navigation allows for 70% success rates for noisy navigators. To reach the same success rates, a secondary sensory system must provide perfect navigation for over 73% of the migratory route, and time integration must integrate over 50 time-steps, indicating that magnetoreceptive animals could benefit from using collective navigation. Finally, we explore the impact of population loss on animals relying on collective navigation. We show that as population density decreases, a greater proportion of individuals fail to reach their destination and that a 50% population reduction can result in up to a 37% decrease in the proportion of individuals completing their migration.

Flow interactions between uncoordinated flapping swimmers give rise to group cohesion.

Many species of fish and birds travel in groups, yet the role of fluid-mediated interactions in schools and flocks is not fully understood. Previous fluid-dynamical models of these collective behaviors assume that all individuals flap identically, whereas animal groups involve variations across members as well as active modifications of wing or fin motions. To study the roles of flapping kinematics and flow interactions, we design a minimal robotic "school" of two hydrofoils swimming in tandem. The flapping kinematics of each foil are independently prescribed and systematically varied, while the forward swimming motions are free and result from the fluid forces. Surprisingly, a pair of uncoordinated foils with dissimilar kinematics can swim together cohesively-without separating or colliding-due to the interaction of the follower with the wake left by the leader. For equal flapping frequencies, the follower experiences stable positions in the leader's wake, with locations that can be controlled by flapping amplitude and phase. Further, a follower with lower flapping speed can defy expectation and keep up with the leader, whereas a faster-flapping follower can be buffered from collision and oscillate in the leader's wake. We formulate a reduced-order model which produces remarkable agreement with all experimentally observed modes by relating the follower's thrust to its flapping speed relative to the wake flow. These results show how flapping kinematics can be used to control locomotion within wakes, and that flow interactions provide a mechanism which promotes group cohesion.

Monopolar flocking of microtubules in collective motion.

Flocking is a fascinating coordinated behavior of living organisms or self-propelled particles (SPPs). Particularly, monopolar flocking has been attractive due to its potential applications in various fields. However, the underlying mechanism behind flocking and emergence of monopolar motion in flocking of SPPs has remained obscured. Here, we demonstrate monopolar flocking of kinesin-driven microtubules, a self-propelled biomolecular motor system. Microtubules with an intrinsic structural chirality preferentially move towards counter-clockwise direction. At high density, the CCW motion of microtubules facilitates monopolar flocking and formation of a spiral pattern. The monopolar flocking of microtubules is accounted for by a torque generated when the motion of microtubules was obstructed due to collisions. Our results shed light on flocking and emergence of monopolar motion in flocking of chiral active matters. This work will help regulate the polarity in collective motion of SPPs which in turn will widen their applications in nanotechnology, materials science and engineering.

Flocking in birds increases annual adult survival in a global analysis.

Adaptive hypotheses for the evolution of group foraging in animals typically invoke enhanced foraging efficiency and reduced predation risk. Net benefits of group foraging in different species should translate into a survival advantage for group members. Despite numerous interspecific studies in birds and mammals, few have documented a survival advantage for group foraging species. Using a large dataset in birds (> 1100 species worldwide), I investigated whether annual adult apparent survival was higher in species that forage in flocks than in solitary species. Using a phylogenetic framework to account for relatedness among species and controlling for known correlates of adult survival in birds such as body size, clutch size, latitude, and diet, I documented a positive effect of flocking on annual adult apparent survival. The increase in survival was less pronounced in occasionally flocking species suggesting that the benefits of group foraging can depend on the frequency of its use. The results highlight how group foraging can increase fitness in animals.

Volvox barberi (Chlorophyceae) actively forms two-dimensional flocks in culture.

Volvox barberi is a multicellular green alga forming spherical colonies of 10,000-50,000 differentiated somatic and germ cells. We observed that in culture, these colonies actively self-organized in just a few minutes into "flocks" that contained as many as 100 colonies moving and rotating collectively for hours. The colonies in flocks formed two-dimensional, irregular, active crystals, that is, geometric lattices within which individual colonies rotated separately. These groupings sometimes disassembled back into individual colonies just as quickly, but in some cases, flocks persisted over several hours. Close inspection of flock formation in the presence of a tracer dye suggested that colony and flock rotations were producing vortices in the fluid medium over a range spanning multiple flock diameters, perhaps providing a physical mechanism for aggregation.

Anisotropic Chitosan Scaffolds Generated by Electrostatic Flocking Combined with Alginate Hydrogel Support Chondrogenic Differentiation.

The replacement of damaged or degenerated articular cartilage tissue remains a challenge, as this non-vascularized tissue has a very limited self-healing capacity. Therefore, tissue engineering (TE) of cartilage is a promising treatment option. Although significant progress has been made in recent years, there is still a lack of scaffolds that ensure the formation of functional cartilage tissue while meeting the mechanical requirements for chondrogenic TE. In this article, we report the application of flock technology, a common process in the modern textile industry, to produce flock scaffolds made of chitosan (a biodegradable and biocompatible biopolymer) for chondrogenic TE. By combining an alginate hydrogel with a chitosan flock scaffold (CFS+ALG), a fiber-reinforced hydrogel with anisotropic properties was developed to support chondrogenic differentiation of embedded human chondrocytes. Pure alginate hydrogels (ALG) and pure chitosan flock scaffolds (CFS) were studied as controls. Morphology of primary human chondrocytes analyzed by cLSM and SEM showed a round, chondrogenic phenotype in CFS+ALG and ALG after 21 days of differentiation, whereas chondrocytes on CFS formed spheroids. The compressive strength of CFS+ALG was higher than the compressive strength of ALG and CFS alone. Chondrocytes embedded in CFS+ALG showed gene expression of chondrogenic markers (COL II, COMP, ACAN), the highest collagen II/I ratio, and production of the typical extracellular matrix such as sGAG and collagen II. The combination of alginate hydrogel with chitosan flock scaffolds resulted in a scaffold with anisotropic structure, good mechanical properties, elasticity, and porosity that supported chondrogenic differentiation of inserted human chondrocytes and expression of chondrogenic markers and typical extracellular matrix.

Local interactions and their group-level consequences in flocking jackdaws.

As one of nature's most striking examples of collective behaviour, bird flocks have attracted extensive research. However, we still lack an understanding of the attractive and repulsive forces that govern interactions between individuals within flocks and how these forces influence neighbours' relative positions and ultimately determine the shape of flocks. We address these issues by analysing the three-dimensional movements of wild jackdaws ( Corvus monedula) in flocks containing 2-338 individuals. We quantify the social interaction forces in large, airborne flocks and find that these forces are highly anisotropic. The long-range attraction in the direction perpendicular to the movement direction is stronger than that along it, and the short-range repulsion is generated mainly by turning rather than changing speed. We explain this phenomenon by considering wingbeat frequency and the change in kinetic and gravitational potential energy during flight, and find that changing the direction of movement is less energetically costly than adjusting speed for birds. Furthermore, our data show that collision avoidance by turning can alter local neighbour distributions and ultimately change the group shape. Our results illustrate the macroscopic consequences of anisotropic interaction forces in bird flocks, and help to draw links between group structure, local interactions and the biophysics of animal locomotion.