Natural Self-organized Systems Research Articles

Fast collective evasion in self-localized swarms of unmanned aerial vehicles

A novel approach for achieving fast evasion in self-localized swarms of unmanned aerial vehicles (UAVs) threatened by an intruding moving object is presented in this paper. Motivated by natural self-organizing systems, the presented approach of fast and collective evasion enables the UAV swarm to avoid dynamic objects (interferers) that are actively approaching the group. The main objective of the proposed technique is the fast and safe escape of the swarm from an interferer discovered in proximity. This method is inspired by the collective behavior of groups of certain animals, such as schools of fish or flocks of birds. These animals use the limited information of their sensing organs and decentralized control to achieve reliable and effective group motion. The system presented in this paper is intended to execute the safe coordination of UAV swarms with a large number of agents. Similar to natural swarms, this system propagates a fast shock of information about detected interferers throughout the group to achieve dynamic and collective evasion. The proposed system is fully decentralized using only onboard sensors to mutually localize swarm agents and interferers, similar to how animals accomplish this behavior. As a result, the communication structure between swarm agents is not overwhelmed by information about the state (position and velocity) of each individual and it is reliable to communication dropouts. The proposed system and theory were numerically evaluated and verified in real-world experiments.

Swarm Robotics: Past, Present, and Future [Point of View

Swarm robotics deals with the design, construction, and deployment of large groups of robots that coordinate and cooperatively solve a problem or perform a task. It takes inspiration from natural self-organizing systems, such as social insects, fish schools, or bird flocks, characterized by emergent collective behavior based on simple local interaction rules [1] , [2] . Typically, swarm robotics extracts engineering principles from the study of those natural systems in order to provide multirobot systems with comparable abilities. This way, it aims to build systems that are more robust, fault-tolerant, and flexible than single robots and that can better adapt their behavior to changes in the environment.

A swarm design paradigm unifying swarm behaviors using minimalistic communication

Numerous nature inspired algorithms have been suggested to enable robotic swarms, mobile sensor networks and other multi-agent systems to exhibit various self-organized behaviors. Swarm intelligence and swarm robotics research have been underway for a few decades and have produced many such algorithms based on natural self-organizing systems. While a large body of research exists for variations and modifications in swarm intelligence algorithms, there have been few attempts to unify the underlying agent level design of these widely varying behaviors. In this work, a design paradigm for a swarm of agents is presented which can exhibit a wide range of collective behaviors at swarm level while using minimalistic single-bit communication at the agent level. The communication in the proposed paradigm is based on waves of ‘ping’-signals inspired by strategies for communication and self organization of slime mold (Dictyostelium discoideum) and fireflies (lampyridae). The unification of common collective behaviors through this Wave Oriented Swarm Paradigm (WOSP) enables the control of swarms with minimalistic communication and yet allowing the emergence of diverse complex behaviors. It is demonstrated both in simulation and using real robotic experiments that even a single-bit communication channel between agents suffices for the design of a substantial set of behaviors. Ultimately, the reader will be enabled to combine different behaviours based on the paradigm to develop a control scheme for individual swarms.

Эргономика сложных систем: типы научной рациональности и энактивизм

The article deals with the problems of control of complex ergatic systems containing symbiotic and environment-oriented forms of control and orientation of interacting agents. The difference in control methods of complex ergatic systems created in the framework of classical and non-classical ergonomics is shown. The conceptual basis of non-classical and post-non-classical ergonomics is presented. The perspectives for the use in the conceptual basis of ergatic control systems the concept of enactivism, which allows to implement the project continuously updated ergonomics of the environment in which the emphasis is on the process of continuous renewal, operational control and correction of parameters of the technical and human parts of the system, taking into account the cyclical processes of Self-organization in actor medium of the actor in achieving objectives. The forms and properties of intellectual formations embodied in organized environments are presented. A number of General definitions of intellect and intellectual symbionts embodied in active ergatic systems arising in the process of combining artificial and natural self-organizing systems of the environment of activity are given.
 The prospects of using conceptual representations of enactivism and constructivism in the management of complex ergatic systems are shown.

Asymmetry and projecting the system of state economic security

The article is devoted to the substantiation of the necessity of impacting the effects of phenomenon of asymmetry in the development of theory and methodology of projecting the system of economic security of the state on the basis of the theory of systems, trans-disciplinary approach, of the law of Structural harmony of systems, the law of the Golden section. Attempt to prove the hypothesis that the phenomenon of asymmetry provides the main risks concerning durability of the system of economic security. It’s necessary to change the paradigm of forming the contour of system of economic security as main condition of base of economy growing.. Imperfection of legislative surroundings, critical terms created by absence of reaction of system of government control under processes of providing of economic security in Ukraine created the loss of the state system, economic and political independence. Height level of shadow economies, as to the complex of different types of the economic activity carried out of scopes of legislative surroundings stipulates asymmetries in economic. Our hypothesis requires further development and using of principles and models of Nature or biogenetic management for development of proof economic systems and system of economic security of state with optimal surplus and asymmetries, for example on the basis of model of phillotacsis. Phenomenon of phillotacsis as natural self-organized systems is mathematically described by the Law of Measure or law of golden section and its derivatives. Modern researches of transdisciplinary character deepened to the level of general acts of form-organization or self-organization of cycle, that present the main interest for the theory of management of complex systems.

Quasi-chemical model of self-assembly and the formation of kinetically controlled structures

A quasi-chemical model of self-assembly among identical objects is proposed. The model rests on two main premises: (a) larger ensembles are more stable and (b) have slower rates of transformation, growth, and decomposition. These statements result from all paired interactions in the considered ensemble. This formulation of self-assembly is shown to be conducive to the formation of large ensembles with sizes distributed normally in a fairly narrow range, and with the concentrations of smaller ensembles being negligible. The existence of two critical points follows from the model. One is a critical concentration that initiates self-assembly in the system when exceeded. The other is a critical ensemble size that sets a threshold for the self-driven growth of ensembles in the system. The growth of ensembles nearly ceases at a point far from equilibrium, and the mean ensemble size and the ensemble’s size distribution are under kinetic control. Stable structures of this kind (with kinetic control of their organization) can serve as models for many natural self-organized systems.

The SOC in cells’ living expectations of Conway’s Game of Life and its extended version

In self-organized systems such as Conway’s Game of Life (CGL). Wikipedia, Conway’s game of the life, https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life., though whether the single cell will survive or die seems unpredictable, the log–log distribution of all cells living frequency satisfies the 1/f linear law, thus meets the Self-organized Criticality(SOC) rule, which not only proves that CGL is a self-organized system, but more significantly, that the chance of living for each cell is spatial heterogeneous, and is statistical fractal.After carried out CGL, the specified iterative period which begins with a random initial condition and ends when it reaches the homeostasis, add up all the states which the living cells are marked by 1s, and the dead are marked by 0s. The resulted sum picture consisting of cells having its gray level representing the living times during the iterative process. By plotting the gray level distribution of the sum picture on log–log scale, the graph indicates the spatial living expectations distributions. Then we find the curve of the graph satisfies the Self-organized Criticality(SOC) rule, showing its linear feature in the intermediate zone, which also has name of 1/f feature.To examine its universality, we designed a more complicated self-organized cellular automata with each cell having five possible states thus the rule table becomes more complicated. As expected, the consequence shows the similar feature, and the linear feature is even more obvious when the similar experiments are carried out.To conclude, it is a new discovery of SOC from a new perspective. And with the self-organized systems expanding to other different rule tables, this feature may still be satisfied.More further, considering the natural self-organized systems of living creatures, the spatial living expectations of different phenotypes may satisfy the 1/f law, too. Though we regard this as an inspirational orientation, the supposition needs more designed experiments to prove.

Molecular self-organization and multiple equilibrium systems

We have compared different types of natural self-organizing systems: crystal-like formation of multi molecular systems were conferred with self-organization in active media and dissipative structure formation. The comparison revealed a common feature of all such systems. They all have bi-(multi-)stable states. We propose a hypothesis that self-organization is impossible in systems that could not have bi-(multi-) stable states.

Evolutionary dynamic optimization: A survey of the state of the art

Optimization in dynamic environments is a challenging but important task since many real-world optimization problems are changing over time. Evolutionary computation and swarm intelligence are good tools to address optimization problems in dynamic environments due to their inspiration from natural self-organized systems and biological evolution, which have always been subject to changing environments. Evolutionary optimization in dynamic environments, or evolutionary dynamic optimization (EDO), has attracted a lot of research effort during the last 20 years, and has become one of the most active research areas in the field of evolutionary computation. In this paper we carry out an in-depth survey of the state-of-the-art of academic research in the field of EDO and other meta-heuristics in four areas: benchmark problems/generators, performance measures, algorithmic approaches, and theoretical studies. The purpose is to for the first time (i) provide detailed explanations of how current approaches work; (ii) review the strengths and weaknesses of each approach; (iii) discuss the current assumptions and coverage of existing EDO research; and (iv) identify current gaps, challenges and opportunities in EDO.

The balance between adaptability and adaptation

In his 1983 book, Adaptability, Michael Conrad explored the quantitative relationship between adaptability and adaptation using the conditional ‘entropy’ of information theory as his primary tool. The conditional entropy can be used to estimate the connectivity of the network of system exchanges, a key indicator of system stability. In fact, the May-Wigner criterion for the stability of linear dynamical systems can be recast using the conditional entropy to help identify the boundary along which adaptability and adaptation are exactly in balance—the ‘edge of chaos’ as it is popularly known. Real data on networks of ecosystem flows indicate that in general these systems do not exist nigh upon the edge of chaos, but rather they populate a much wider ‘window of vitality’ that exists between the realms of chaotic and deterministic dynamics. It appears that the magnitudes of network flows within this region are distributed in power law fashion. The theory also suggests that an absolute limit to the connectivity of natural self-organizing systems exists, at approximately 3.015 effective connections per node.

From molecules to mindfulness

Fractal time fluctuations of the spectral “1/f” form are universal in natural self-organizing systems. Neurobiology is uniquely infused with fractal fluctuations in the form of statistically self-similar clusters or bursts on all levels of description from molecular events such as protein chain fluctuations, ion channel currents and synaptic processes to the behaviors of neural ensembles or the collective behavior of Internet users. It is the thesis of this essay that the brain self-organizes via a vertical collation of these spontaneous events in order to perceive the world and generate adaptive behaviors. REM sleep, which coalesces from self-similar clusters of burst-within-burst behavior during ontogeny, is essential to cognitive-emotional function, and has recurrent fractal organization. Empirical fMRI observations further support the association of fractal fluctuations in the temporal lobes, brainstem and cerebellum during the expression of emotional memory, spontaneous fluctuations of thought and meditative practice. Cognitive-emotional integration arises as amygdaloid-brainstem-cerebellar systems harmonize the vertical “1/f” symphony of coupled isochronous cortical oscillations in the pursuit of mindfulness.