We have proposed to use some features of swarm behaviours in modelling business processes. Due to these features we deal with a propagation of business processes in all accessible directions. This propagation is involved into our formalization instead of communicating sequential processes. As a result, we have constructed a business process diagram language based on the swarm behavior and an extension of that language in the form of reflexive management language.

Explaining the seizure of power by the National Socialist Party and the totalitarian workings of the Nazi regime in the Third Reich is still difficult not only with respect to the atrocities committed but also to understanding whether the German population and society had to be terrorized into complying with the regime or were part and parcel of it. The paper introduces a notion of swarm to advance the idea that the German population was terrorized into a deliberate compliance with (...) the regime. The notion of swarm is sociologically controlled by a complementary notion of form, which serves to reconstruct and model the social calculus realized by the swarm to differentiate and reproduce itself inside a complex society. The data I use are the results of historical research done in the last 60 years. (shrink)

Because of the lack of interaction between seeking mode cats and tracking mode cats in cat swarm optimization, its convergence speed and convergence accuracy are affected. An information interaction strategy is designed between seeking mode cats and tracking mode cats to improve the convergence speed of the CSO. To increase the diversity of each cat, a top-N learning strategy is proposed during the tracking process of tracking mode cats to improve the convergence accuracy of the CSO. On ten standard test (...) functions, the average values, standard deviations, and optimal values of the proposed algorithm with different N values are compared with the original CSO algorithm and the adaptive cat swarm algorithm based on dynamic search. Experimental results show that the global search ability and the convergence speed of the proposed algorithm are significantly improved on all test functions. The proposed two strategies will improve the convergence accuracy and convergence speed of CSO greatly. (shrink)

When animals share decisions with others, they pool personal information, offset individual errors and, thereby, increase decision accuracy. This is termed ‘swarm intelligence.’ But what if those decisions involve conflicts of interest between individual decision-makers? Should animals share decisions with individuals whose goals are different from, and partially in conflict with, their own? A group decision model developed by Larissa Conradt and colleagues finds that, contrary to intuition, conflicting goals often increase both decision accuracy and the individual gains derived from (...) shared decisions. Thus, conflicts of interest, far from hampering effective decision making, can actually improve decision outcomes for all stakeholders, as long as they also have some goals in common. By contrast, conflict-free decisions shared by animals which all have the same goals are often surprisingly poor. (shrink)

Traditional art history equates the production of the memes of visual art exclusively with individual consciousness. An evolutionary art history looks also at the patterns into which art-memes flow patterns that display striking synchronicities of cultural motivation, both within the arts themselves and between the arts and sciences parallel patterns of collective memetic behaviour. We are all familiar with short-wave collective behaviour: football fans, evangelist meetings, political demonstrations, rioting crowds and panicking troops all display it. This paper is concerned with (...) long-wave collective behaviour, as evidenced in the migration of Western elite culture from the open to the closed meme in the arts and sciences of the Renaissance period, or again in the reciprocal cultural migration from closed to open memes going on in the arts and sciences at the present time. How do we explain this swarming of the memes, such that artistic and scientific communication, despite their explicitly different forms, seem invisibly joined at the hip? Why do our memes rock'n'roll topologically between open and closed states? The paper suggests that memetic swarming the synchronization of our memes in alternating open and closed states may be an expression of the sensitivity of our consciousness to the changing dynamics of our own relationship with the planetary biosphere through ecological evolution. If so, the ultimate driver of memetic swarming may be an algorithm as commonplace and as universal as the figureground opposition: linking our evolution with our memes by way of a simple principle of reciprocity, such that consciousness will tend to output closed memes in periods of open evolution, and, reciprocally, closed memes in periods of open evolution. (shrink)

The efficiency of distribution networks is hugely affected by active and reactive power flows in distribution electric power systems. Currently, distributed generators (DGs) of energy are extensively applied to minimize power loss and improve voltage deviancies on power distribution systems. The best position and volume of DGs produce better power outcomes. This work prepares a new hybrid SSA–GWO metaheuristic optimization algorithm that combines the salp swarm algorithm (SSA) and the gray wolf optimizer (GWO) algorithm. The SSA–GWO algorithm ensures generating the (...) best size and site of one and multi-DGs on the radial distribution network to decrease real power losses (RPL) (kW) on lines and resolve voltage deviancies. Our novel algorithm is executed on IEEE 123-bus radial distribution test systems. The results confirm the success of the suggested hybrid SSA–GWO algorithm compared with implementing the SSA and GWO individually. Through the proposed SSA–GWO algorithm, the study decreases the RPL and improves the voltage profile on distribution networks with multiple DGs units. (shrink)

This contribution examines the media history of swarm research and the significance of swarming techniques to current socio-technological processes. It explores how the procedures of swarm intelligence should be understood in relation to the concept of cultural techniques. This brings the concept into proximity with recent debates in posthuman (media) theory, animal studies and software studies. Swarms are conceptualized as zootechnologies that resist methods of analytical investigation. Synthetic swarms first emerged as operational collective structures by means of the reciprocal (...) computerization of biology and biologization of computer science. In a recursive loop, swarms inspired agent-based modelling, which in turn provided biological researchers with enduring knowledge about dynamic collectives. This conglomerate led to the development of advanced, software-based ‘particle systems’. Swarm intelligence has become a fundamental cultural technique related to dynamic processes and an effective metaphor for the collaborative efforts of society. (shrink)

Insects and ‘the swarm’ as metaphors and objects of research have inspired works in the genres of science fiction and horror; social and political theorists; and the development of war-fighting technologies such as ‘drone swarms’, which function as robot/insect hybrids. Contemporary developments suggest that the future of warfare will not be ‘robots’ as technological, individualised substitutions for idealised (masculine) warfighters, but warfighters understood as swarms: insect metaphors for non-centrally organised problem-solvers that will become technologies of racialisation. As such, contemporary feminist (...) analysis requires an analysis of the politics of life and death in the insect and the swarm, which, following Braidotti (2002), cannot be assumed to be a mere metaphor or representation of political life, but an animating materialist logic. The swarm is not only a metaphor but also a central mode of biopolitical and necropolitical war, with the ‘terrorist’ enemy represented as swarmlike as well. In analysing the relations of assemblage and antagonism in the war ontologies of the drone swarm, I seek inspiration from what Hayles (1999, p. 47) describes as a double vision that ‘looks simultaneously at the power of simulation and at the materialities that produce it’. I discuss various representations and manifestations of swarms and insect life in science/speculative fiction, from various presentations of the ‘Borg’ in Star Trek (1987–1994, 1995–2001, 1996), Alien (1979) and The Fly (1958, 1986) to more positive representations of the ‘becoming-insect’ as possible feminist Utopia in Gilman's Herland (2015 [1915]) and Tiptree's Houston, Houston, Do You Read? (1989 [1976]). Posthuman warfare also contains the possibilities of both appropriating and rewriting antagonisms of masculine and feminine in the embodiment of the subject of war in the swarm. This piece seeks to analyse new ways of feminist theorising of the relations of power and violence in the embodiment of war as the swarm. (shrink)

In the agriculture development and growth, the efficient machinery and equipment plays an important role. Various research studies are involved in the implementation of the research and patents to aid the smart agriculture and authors and reviewers that machine leaning technologies are providing the best support for this growth. To explore machine learning technology and machine learning algorithms, the most of the applications are studied based on the swarm intelligence optimization. An optimized V3CFOA-RF model is built through V3CFOA. The algorithm (...) is tested in the data set collected concerning rice pests, later analyzed and compared in detail with other existing algorithms. The research result shows that the model and algorithm proposed are not only more accurate in recognition and prediction, but also solve the time lagging problem to a degree. The model and algorithm helped realize a higher accuracy in crop pest prediction, which ensures a more stable and higher output of rice. Thus they can be employed as an important decision-making instrument in the agricultural production sector. (shrink)

ArgumentDiscussions of the scientific uses of moving-image technologies have emphasized applications that culminated in static images, such as the chronophotographic decomposition of movement into discrete and measurable instants. The projection of movement, however, was also an important capability of moving-image technologies that scientists employed in a variety of ways. Views through the microscope provide a particularly sustained and prominent instance of the scientific uses of the moving image. The category of “education” subsumes theses various scientific uses, providing a means by (...) which to bridge the cultures of scientific and popular scientific moving images. (shrink)

Considering the current advancements in biometric sensors and other related technologies, as well as the use of bio-inspired models for AI improvements, we can infer that the swarm intelligence paradigm can be implemented in human daily spheres through the connectivity between user gadgets connected to the Internet of Things. This is a first step towards a real Ambient Intelligence, but also of a Global Intelligence. This unconscious connectivity may alter the way by which we feel the world. Besides, with the (...) arrival of new augmented ways of capturing and providing information or radical new ways of expanding our bodies, we can be very close to a change which may radically affect our experience of ourselves and of the feeling of collectivity. We call it the techno-phenomenological turn. We show social implications, present challenges, and and open questions for the new kind of swarm intelligence-enhanced society, and provide the taxonomy of the field of study. We will also explore the possible roadmaps of this next possible situation. (shrink)

Name der Zeitschrift: Kierkegaard Studies Yearbook Jahrgang: 19 Heft: 1 Seiten: 231-252.

Günter Wagner’s Homology, Genes, and Evolutionary Innovation collects and synthesizes a vast array of empirical data, theoretical models, and conceptual analysis to set out a progressive research program with a central theoretical commitment: the genetic theory of homology. This research program diverges from standard approaches in evolutionary biology, provides sharpened contours to explanations of the origin of novelty, and expands the conceptual repertoire of evolutionary developmental biology. I concentrate on four aspects of the book in this essay review: the genetic (...) theory of homology and character identity networks; the implications for how we explain evolutionary novelties; the expanded set of concepts surrounding homology, and the epistemological conflicts between Wagner’s viewpoint and functionally-oriented evolutionary biology, as well as differences with other Evo–devo researchers. Together these have ramifications for how we interpret different explanatory approaches to evolutionary phenomena and understand relationships between the usefulness of concepts and the reality they represent. (shrink)

Efficient community detection in a complex network is considered an interesting issue due to its vast applications in many prevailing areas such as biology, chemistry, linguistics, social sciences, and others. There are several algorithms available for network community detection. This study proposed the Sigmoid Fish Swarm Optimization algorithm to discover efficient network communities. Our proposed algorithm uses the sigmoid function for various fish moves in a swarm, including Prey, Follow, Swarm, and Free Move, for better movement and community detection. The (...) proposed SiFSO algorithm’s performance is tested against state-of-the-art particle swarm optimization algorithms in Q-modularity and normalized mutual information. The results showed that the proposed SiFSO algorithm is 0.0014% better in terms of Q-modularity and 0.1187% better in terms of NMI than the other selected algorithms. (shrink)

Physarum polycephalum, a unicellular and multiheaded slime mould, can form highly efficient networks connecting separated food sources during the process of foraging. These adaptive networks exhibit a unique characteristic in that they are optimized without the control of a central consciousness. Inspired by this phenomenon, we present an efficient exploration and navigation strategy for a swarm of robots, which exploits cooperation and self-organisation to overcome the limited abilities of the individual robots. The task faced by the robots consists in the (...) exploration of an unknown environment in order to find a path between two distant target areas. For the proposed algorithm, we experimentally present robustness tests and obstacle tests conducted to analyse the performance of our algorithm and compare the proposed algorithm with other swarm robot foraging algorithms that also focus on the path formation task. This work has certain significance for the research of swarm robots and Physarum polycephalum. For the research of swarm robotics, our algorithm not only can lead multirobot as a whole to overcome the limitations of very simple individual agents but also can offer better performance in terms of search efficiency and success rate. For the research of Physarum polycephalum, this work is the first one combining swarm robots and Physarum polycephalum. It also reveals the potential of the Physarum polycephalum foraging principle in multirobot systems. (shrink)

Flow prediction in a vegetated channel has been extensively studied in the past few decades. A number of equations that essentially differ from each other in derivation and form have been developed. Because the process is extremely complex, getting the deterministic or analytical form of the process phenomena is too difficult. Hybrid neural network model is particularly useful in modeling processes where an adequate knowledge of the physics is limited. This hybrid model is presented here as a complementary tool to (...) model channel flow–vegetation interactions in submerged vegetation conditions. The hybrid model is used to overcome the local minima limitations of a feed-forward neural network. The prediction capability of model has been found to be better than past empirical predictors. The model developed herein showed significantly better results in several model performance criteria compared with empirical models. (shrink)

Economic dispatch plays an important role in power system operation, since it can decrease the operating cost, save energy resources, and reduce environmental load. This paper presents an improved particle swarm optimization called biogeography-based learning particle swarm optimization for solving the ED problems involving different equality and inequality constraints, such as power balance, prohibited operating zones, and ramp-rate limits. In the proposed BLPSO, a biogeography-based learning strategy is employed in which particles learn from each other based on the quality of (...) their personal best positions, and thus it can provide a more efficient balance between exploration and exploitation. The proposed BLPSO is applied to solve five ED problems and compared with other optimization techniques in the literature. Experimental results demonstrate that the BLPSO is a promising approach for solving the ED problems. (shrink)

Metaheuristic algorithms are often applied to global function optimization problems. To overcome the poor real-time performance and low precision of the basic salp swarm algorithm, this paper introduces a novel hybrid algorithm inspired by the perturbation weight mechanism. The proposed perturbation weight salp swarm algorithm has the advantages of a broad search scope and a strong balance between exploration and exploitation and retains a relatively low computational complexity when dealing with numerous large-scale problems. A new coefficient factor is introduced to (...) the basic salp swarm algorithm, and new update strategies for the leader position and the followers are introduced in the search phase. The new leader position updating strategy has a specific bounded scope and strong search performance, thus accelerating the iteration process. The new follower updating strategy maintains the diversity of feasible solutions while reducing the computational load. This paper describes the application of the proposed algorithm to low-dimension and variable-dimension functions. This paper also presents iteration curves, box-plot charts, and search-path graphics to verify the accuracy of the proposed algorithm. The experimental results demonstrate that the perturbation weight salp swarm algorithm offers a better search speed and search balance than the basic salp swarm algorithm in different environments. (shrink)

Despite the ubiquity of bees in Dickinson’s work, most interpreters denigrate her nature poems. But following several recent scholars, I identify Nietzschean/Dionysian overtones in the bee poems and suggest the figure of bees/hive/queen illuminates as feminist key to her corpus. First, (a) the bee’s sting represents martyred death; (b) its gold, immortality; (c) its tongue, the “lesbian phallus”; (d) its wings, poetic power; (e) its buzz, poetic melody, and (f) its organism, a joyful Dionysian Susan (her sister-in-law and love interest) (...) to Emily’s flower. Second, the hive represents her individual poems (with slants/dashes as stingers, wings as hymn meter, honey as rhymes, variant words as exiled bees, and accompanying flowers their Darwinian coevolution with bees), constituting her writing persona as a multi-voiced self-swarm, as organized in the apiary of her letters and fascicles. And third, the queen represents her Western cultural and religious inheritance wherein bees are symbols of the soul, reincarnation, poetic-philosophical vocation, and a Nietzschean, trans-Dionysian naturalist ontology—symbolized by apiarian Artemis. (shrink)

Effective and personalized treatment relies heavily on skin disease categorization. In the stratification of skin disorders, it is crucial to identify the subtypes of illnesses to provide an efficient therapy. To attain this aim, researchers have focused their attention on cluster algorithms for the stratification of skin disorders in recent decades. But, cluster algorithms have real-world drawbacks, including experimental noises, a large number of dimensions, and a poor ability to comprehend. Cluster algorithms, in particular, determine the quality of clusters using (...) a single internal evaluation operation in the majority of cases. A single internal assessment procedure is difficult to design and robust for all datasets, which is a problem. The multi-objective particle swarm obtained high sensitivity in the existing work, but it is not able to anticipate all kinds of classes. An optimized cluster distance parameter for K-means clustering is determined using a hybrid particle swarm and moth flame optimization. Multi-objective is guided by two cluster value indices, including the K-means clustering misclassification rate and neural network classification rate. Hybrid PSO will solve the multi-objective problem to identify the optimal cluster for clustering. On the dermatological dataset from the UCI repository, MATLAB R2020a will be used to evaluate the proposed method. This will be followed by an evaluation of the proposed method’s performance using the cluster evaluation indices. (shrink)

This article considers Jussi Parikka’s Insect Media: An Archaeology of Animals and Technology and its place within the broader context of neomaterialist philosophy. The question of Insect Media, and indeed of neomaterialism more generally, can be summarized as follows: how might one open oneself to radically alien durations, while remaining politically sensitive to the concomitant risk of technocapitalist capture? Moving through the wide range of subjects engaged with by Parikka, from entomology and cinema to the most advanced forms of programming (...) ecologies, I focus on Parikka’s organizing notion of insects as figuring the molecular disruption of the phantasmatic molar body. For Parikka, it is the swarm that serves as his privileged example, which he locates at the intersection of animal studies, posthumanism and media theory. After outlining Parikka’s important reworking of Bergson’s conception of instinct, understood as ‘intensities’, which functions equally well within the domain of new media, and some of its implications for neo-Darwinism, I then consider Parikka’s ‘melodic’ conception of both nature and technology. Such a conception, I suggest, is problematic in its conflation of nonhuman animals with, for example, software, technologies, viruses and parasites. This in turn puts into question Parikka’s ‘use’ of insects in relation to the claim, common to neomaterialism in general, to have moved beyond an anthropocentric viewpoint. Rather, I argue, such a conception rebuilds a humanist enclosure, albeit one in which, following Guattari, subjectivity can no longer be identified with the individual. Insofar as Parikka designates every nonhuman animal and every machine as beings prior to language and thus prior to intelligence, the non-unitary subject is as a result restricted to the experiencing human subject. This, as Eugene Thacker points out, has serious political implications as regards the attribution of value, or not, to this or that life. However, insofar as Parikka considers instinct as habitual rather than as predetermined and, moreover, extends it to technical beings, I suggest that such a placing of instinct as ‘prelinguistic’ cannot be maintained. By way of conclusion, I appeal for the opening of a dialogue between neomaterialism and deconstruction, with its focus upon language understood in a much broader sense. (shrink)

In order to solve the shortcomings of particle swarm optimization in solving multiobjective optimization problems, an improved multiobjective particle swarm optimization algorithm is proposed. In this study, the competitive strategy was introduced into the construction process of Pareto external archives to speed up the search process of nondominated solutions, thereby increasing the speed of the establishment of Pareto external archives. In addition, the descending order of crowding distance method is used to limit the size of external archives and dynamically adjust (...) particle parameters; in order to solve the problem of insufficient population diversity in the later stage of algorithm iteration, time-varying Gaussian mutation strategy is used to mutate the particles in external archives to improve diversity. The simulation experiment results show that the improved algorithm has better convergence and stability than the other compared algorithms. (shrink)

Uninhabited combat air vehicle path planning is a complicated, high-dimension optimization problem. To solve this problem, we present in this article an improved glowworm swarm optimization algorithm based on the particle swarm optimization algorithm, which we call the PGSO algorithm. In PGSO, the mechanism of a glowworm individual was modified via the individual generation mechanism of PSO. Meanwhile, to improve the presented algorithm’s convergence rate and computational accuracy, we reference the idea of parallel hybrid mutation and local search near the (...) global optimal location. To prove the performance of the proposed algorithm, PGSO was compared with 10 other population-based optimization methods. The experiment results show that the proposed approach is more effective in UCAV path planning than most of the other meta-heuristic algorithms. (shrink)

In _Facing the Planetary_ William E. Connolly expands his influential work on the politics of pluralization, capitalism, fragility, and secularism to address the complexities of climate change and to complicate notions of the Anthropocene. Focusing on planetary processes—including the ocean conveyor, glacier flows, tectonic plates, and species evolution—he combines a critical understanding of capitalism with an appreciation of how such nonhuman systems periodically change on their own. Drawing upon scientists and intellectuals such as Lynn Margulis, Michael Benton, Alfred North Whitehead, (...) Anna Tsing, Mahatma Gandhi, Wangari Maathai, Pope Francis, Bruno Latour, and Naomi Klein, Connolly focuses on the gap between those regions creating the most climate change and those suffering most from it. He addresses the creative potential of a "politics of swarming" by which people in different regions and social positions coalesce to reshape dominant priorities. He also explores how those displaying spiritual affinities across differences in creed can energize a militant assemblage that is already underway. (shrink)

Ethical reflections on military robotics can be enriched by a better understanding of the nature and role of these technologies and by putting robotics into context in various ways. Discussing a range of ethical questions, this paper challenges the prevalent assumptions that military robotics is about military technology as a mere means to an end, about single killer machines, and about “military” developments. It recommends that ethics of robotics attend to how military technology changes our aims, concern itself not only (...) with individual robots but also and especially with networks and swarms, and adapt its conceptions of responsibility to the rise of such cloudy and unpredictable systems, which rely on decentralized control and buzz across many spheres of human activity. (shrink)

Condorcet's jury theorem shows that when the members of a group have noisy but independent information about what is best for the group as a whole, majority decisions tend to outperform dictatorial ones. When voting is supplemented by communication, however, the resulting interdependencies between decision makers can strengthen or undermine this effect: they can facilitate information pooling, but also amplify errors. We consider an intriguing non-human case of independent information pooling combined with communication: the case of nest-site choice by honeybee (...) (Apis mellifera) swarms. It is empirically well documented that when there are different nest sites that vary in quality, the bees usually choose the best one. We develop a new agent-based model of the bees' decision process and show that its remarkable reliability stems from a particular interplay of independence and interdependence between the bees. (shrink)

Radiography images are widely utilized in the health sector to recognize the patient health condition. The noise and irrelevant region information minimize the entire disease detection accuracy and computation complexity. Therefore, in this study, statistical Kolmogorov–Smirnov test has been integrated with wavelet transform to overcome the de-noising issues. Then the cat swarm-optimized deep belief network is applied to extract the features from the affected region. The optimized deep learning model reduces the feature training cost and time and improves the overall (...) disease detection accuracy. The network learning process is enhanced according to the AdaDelta learning process, which replaces the learning parameter with a delta value. This process minimizes the error rate while recognizing the disease. The efficiency of the system evaluated using image retrieval in medical application dataset. This process helps to determine the various diseases such as breast, lung, and pediatric studies. (shrink)

Rohwer and Marris’s exploration of grounds for a prima facie duty to preserve the genetic integrity of wild species makes two important contributions to the environmental ethics literature. While n...

Considering the highly complex structure of quantum chaos and the nonstationary characteristics of speech signals, this paper proposes a quantum chaotic encryption and quantum particle swarm extraction method based on an underdetermined model. The proposed method first uses quantum chaos to encrypt the speech signal and then uses the local mean decomposition method to construct a virtual receiving array and convert the underdetermined model to a positive definite model. Finally, the signal is extracted using the Levi flight strategy based on (...) kurtosis and the quantum particle swarm optimization optimized by the greedy algorithm. The bit error rate and similarity coefficient of the voice signal are extracted by testing the source voice signal SA1, SA2, and SI943 under different SNR, and the similarity coefficient, uncertainty, and disorder of the observed signal and the source voice signal SA1, SA2, and SI943 verify the effectiveness of the proposed speech signal extraction method and the security of quantum chaos used in speech signal encryption. (shrink)

Based on the adaptive particle swarm algorithm and error backpropagation neural network, this paper proposes methods for different styles of music classification and migration visualization. This method has the advantages of simple structure, mature algorithm, and accurate optimization. It can find better network weights and thresholds so that particles can jump out of the local optimal solutions previously searched and search in a larger space. The global search uses the gradient method to accelerate the optimization and control the real-time generation (...) effect of the music style transfer, thereby improving the learning performance and convergence performance of the entire network, ultimately improving the recognition rate of the entire system, and visualizing the musical perception. This kind of real-time information visualization is an artistic expression form, in which artificial intelligence imitates human synesthesia, and it is also a kind of performance art. Combining traditional music visualization and image style transfer adds specific content expression to music visualization and time sequence expression to image style transfer. This visual effect can help users generate unique and personalized portraits with music; it can also be widely used by artists to express the relationship between music and vision. The simulation results show that the method has better classification performance and has certain practical significance and reference value. (shrink)

The spontaneous organization of collective activities in animal groups and societies has attracted a considerable amount of attention over the last decade. This kind of coordination often permits group‐living species to achieve collective tasks that are far beyond single individuals' capabilities. In particular, a key benefit lies in the integration of partial knowledge of the environment at the collective level. In this contribution, we discuss various self‐organization phenomena in animal swarms and human crowds from the point of view of information (...) exchange among individuals. In particular, we provide a general description of collective dynamics across species and introduce a classification of these dynamics not only with respect to the way information is transferred among individuals but also with regard to the knowledge processing at the collective level. Finally, we highlight the fact that the individual’s ability to learn from past experiences can have a feedback effect on the collective dynamics, as experienced with the development of behavioral conventions in pedestrian crowds. (shrink)

We present a simple distributed concept that appears to insinuate SWARM behavior in a collection of mobile platforms. The control is based on the inter-mobile platform communication links’ signal-to-noise ratio. This double use of communications is a natural linkage for SWARM behavior.