19. Robustness in Natural Systems and Self-Organization

2013 ◽  
pp. 297-309
Keyword(s):  
Self Organization ◽  
Natural Systems

scholarly journals SELF-ORGANIZATION IN COMPLEX SYSTEMS AS DECISION MAKING

2014 ◽  
Vol 17 (03n04) ◽  
pp. 1450016 ◽  
Author(s):  
V. I. YUKALOV ◽  
D. SORNETTE
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Mathematical Formulation ◽  
Conditional Entropy ◽  
Self Organization ◽  
Entropy Maximization ◽  
Natural Systems ◽  
Macroscopic States ◽  
System States ◽  
Statistical Systems

The idea is advanced that self-organization in complex systems can be treated as decision making (as it is performed by humans) and, vice versa, decision making is nothing but a kind of self-organization in the decision maker nervous systems. A mathematical formulation is suggested based on the definition of probabilities of system states, whose particular cases characterize the probabilities of structures, patterns, scenarios, or prospects. In this general framework, it is shown that the mathematical structures of self-organization and of decision making are identical. This makes it clear how self-organization can be seen as an endogenous decision making process and, reciprocally, decision making occurs via an endogenous self-organization. The approach is illustrated by phase transitions in large statistical systems, crossovers in small statistical systems, evolutions and revolutions in social and biological systems, structural self-organization in dynamical systems, and by the probabilistic formulation of classical and behavioral decision theories. In all these cases, self-organization is described as the process of evaluating the probabilities of macroscopic states or prospects in the search for a state with the largest probability. The general way of deriving the probability measure for classical systems is the principle of minimal information, that is, the conditional entropy maximization under given constraints. Behavioral biases of decision makers can be characterized in the same way as analogous to quantum fluctuations in natural systems.

scholarly journals Review of Anaerobic Digestion Modeling and Optimization Using Nature-Inspired Techniques

Processes ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 953 ◽  
Author(s):  
Anjali Ramachandran ◽  
Rabee Rustum ◽  
Adebayo J. Adeloye
Keyword(s):  
Artificial Intelligence ◽  
Parallel Computing ◽  
Anaerobic Digestion ◽  
Soft Computing ◽  
Optimal Solution ◽  
Self Organization ◽  
Economic Factors ◽  
Comprehensive Review ◽  
Natural Systems ◽  
Engineered Systems

Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems. For soft computing applications, nature-inspired techniques have several advantages, including scope for parallel computing, dynamic behavior, and self-organization. This paper presents a comprehensive review of such techniques and their application in anaerobic digestion modeling. We compiled and synthetized the literature on the applications of nature-inspired techniques applied to anaerobic digestion. These techniques provide a balance between diversity and speed of arrival at the optimal solution, which has stimulated their use in anaerobic digestion modeling.

Ansatz for Dynamical Hierarchies

2001 ◽  
Vol 7 (4) ◽  
pp. 329-353 ◽  
Author(s):  
Steen Rasmussen ◽  
Nils A. Baas ◽  
Bernd Mayer ◽  
Martin Nilsson
Keyword(s):  
Self Assembly ◽  
Lattice Gas ◽  
Three Dimensional ◽  
Self Organization ◽  
Emergent Properties ◽  
Simulation Framework ◽  
Natural Systems ◽  
Polymer Aggregates ◽  
Physicochemical Simulation ◽  
Different Levels

Complex, robust functionalities can be generated naturally in at least two ways: by the assembly of structures and by the evolution of structures. This work is concerned with spontaneous formation of structures. We define the notion of dynamical hierarchies in natural systems and show the importance of this particular kind of organization for living systems. We then define a framework that enables us to formulate, investigate, and manipulate such dynamical hierarchies. This framework allows us to simultaneously investigate different levels of description together with their interrelationship, which is necessary to understand the nature of dynamical hierarchies. Our framework is then applied to a concrete and very simple formal, physicochemical, dynamical hierarchy involving water and monomers at level one, polymers and water at level two, and micelles (polymer aggregates) and water at level three. Formulating this system as a simple two-dimensional molecular dynamics (MD) lattice gas allows us within one dynamical system to demonstrate the successive emergence of two higher levels (three levels all together) of robust structures with associated properties. Second, we demonstrate how the framework for dynamical hierarchies can be used for realistic (predictive) physicochemical simulation of molecular self-assembly and self-organization processes. We discuss the detailed process of micellation using the three-dimensional MD lattice gas. Finally, from these examples we can infer principles about formal dynamical hierarchies. We present an ansatz for how to generate robust, higher-order emergent properties in formal dynamical systems that is based on a conjecture of a necessary minimal complexity within the fundamental interacting structures once a particular simulation framework is chosen.

scholarly journals METAPHYSICS AND INTERDISCIPLINARY MODELS

Metaphysics ◽  
2021 ◽  
pp. 92-117
Author(s):  
O. B Balakshin
Keyword(s):  
Chemical Elements ◽  
Structural Parameters ◽  
Self Organization ◽  
Self Similarity ◽  
Natural Systems ◽  
Material Systems ◽  
The World ◽  
External Conditions ◽  
Health And Disease ◽  
The Universe

Metaphysical numerical methods of self-organization of natural systems of Nature, their interdisciplinary connections and models are investigated. They are confirmed by a number of examples and facts, predict informational beginnings and the sequence of formation of material systems of Nature. The facts relate to the chemical elements of the Universe, plants and living systems in health and disease. Their structural periods of self-organization coincide or have common roots. Systems have a “end-to-end” similarity of everything with everything on the basis of the principle of self-similarity and unlimited two-way connection of structural parameters. It is shown that the Abelian Group, the basis of self-organization of systems, allows you to systematize models based on the unity of their origins. The concept of natural self-organization of systems predicts the chemical elements of the Universe and the existence (or appearance) of other civilizations in the world under similar external conditions.

scholarly journals Trade-off shapes diversity in eco-evolutionary dynamics

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Farnoush Farahpour ◽  
Mohammadkarim Saeedghalati ◽  
Verena S Brauer ◽  
Daniel Hoffmann
Keyword(s):  
Competitive Ability ◽  
Evolutionary Dynamics ◽  
Evolutionary Model ◽  
Self Organization ◽  
Mixed System ◽  
Replication Rate ◽  
Trade Off ◽  
Natural Systems ◽  
Sharp Phase Transition ◽  
Trait Space

We introduce an Interaction- and Trade-off-based Eco-Evolutionary Model (ITEEM), in which species are competing in a well-mixed system, and their evolution in interaction trait space is subject to a life-history trade-off between replication rate and competitive ability. We demonstrate that the shape of the trade-off has a fundamental impact on eco-evolutionary dynamics, as it imposes four phases of diversity, including a sharp phase transition. Despite its minimalism, ITEEM produces a remarkable range of patterns of eco-evolutionary dynamics that are observed in experimental and natural systems. Most notably we find self-organization towards structured communities with high and sustained diversity, in which competing species form interaction cycles similar to rock-paper-scissors games.

scholarly journals Determinism, chaos, self-organization and entropy

2016 ◽  
Vol 88 (2) ◽  
pp. 1151-1164 ◽  
Author(s):  
JOSÉ PONTES
Keyword(s):  
Self Organization ◽  
Human Being ◽  
New Paradigm ◽  
Natural Systems ◽  
Progressive Loss ◽  
Evolution Laws ◽  
Biological Physics ◽  
The Individual ◽  
Emergence Of Life ◽  
Nonlinear Nature

ABSTRACT We discuss two changes of paradigms that occurred in science along the XXth century: the end of the mechanist determinism, and the end of the apparent incompatibility between biology, where emergence of order is law, and physics, postulating a progressive loss of order in natural systems. We recognize today that three mechanisms play a major role in the building of order: the nonlinear nature of most evolution laws, along with distance to equilibrium, and with the new paradigm, that emerged in the last forty years, as we recognize that networks present collective order properties not found in the individual nodes. We also address the result presented by Blumenfeld (L.A. Blumenfeld, Problems of Biological Physics, Springer, Berlin, 1981) showing that entropy decreases resulting from building one of the most complex biological structures, the human being, are small and may be trivially compensated for compliance with thermodynamics. Life is made at the expense of very low thermodynamic cost, so thermodynamics does not pose major restrictions to the emergence of life. Besides, entropy does not capture our idea of order in biological systems. The above questions show that science is not free of confl icts and backlashes, often resulting from excessive extrapolations.

scholarly journals The principles of collective animal behaviour

2005 ◽  
Vol 361 (1465) ◽  
pp. 5-22 ◽  
Author(s):  
D.J.T Sumpter
Keyword(s):  
Collective Behaviour ◽  
Self Organization ◽  
Termite Mounds ◽  
Physical Systems ◽  
Natural Systems ◽  
Complex Adaptive ◽  
Ant Trail ◽  
The Individual ◽  
Simple Sets ◽  
Animal Societies

In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society.

OVERVIEW OF THE METHODS FOR SELF-ORGANIZATION IN SWARM ROBOTICS

2020 ◽  
Vol 70 (2) ◽  
Author(s):  
Aleksandar Marinchev
Keyword(s):  
Swarm Robotics ◽  
Self Organization ◽  
Common Phenomenon ◽  
Natural Systems ◽  
Simple Rules ◽  
Swarm Coordination

Self-organization is a common phenomenon observed in many natural and artificial systems. The overall coordinated behavior of the system is due to simple rules for interaction between its components. Thanks to these properties, self-organization plays a key role in swarm robotics, as it allows swarm coordination with minimal complexity of individual robots. This paper reviews the methods and tools for self-organization that are used in swarm robotics or are found in natural systems.

Effect of Iron Limitation on the Ultrastructure of Agmenellum Quadruplicatum

1981 ◽  
Vol 39 ◽  
pp. 410-411
Author(s):  
L. P. Hardie ◽  
D. L. Balkwill ◽  
S. E. Stevens
Keyword(s):  
Growth Medium ◽  
Green Alga ◽  
Natural Habitat ◽  
Iron Limitation ◽  
Natural Environments ◽  
Blue Green Alga ◽  
Marine Cyanobacterium ◽  
Natural Systems ◽  
Thin Sectioning ◽  
Agmenellum Quadruplicatum

Agmenellum quadruplicatum is a unicellular, non-nitrogen-fixing, marine cyanobacterium (blue-green alga). The ultrastructure of this organism, when grown in the laboratory with all necessary nutrients, has been characterized thoroughly. In contrast, little is known of its ultrastructure in the specific nutrient-limiting conditions typical of its natural habitat. Iron is one of the nutrients likely to limit this organism in such natural environments. It is also of great importance metabolically, being required for both photosynthesis and assimilation of nitrate. The purpose of this study was to assess the effects (if any) of iron limitation on the ultrastructure of A. quadruplicatum. It was part of a broader endeavor to elucidate the ultrastructure of cyanobacteria in natural systemsActively growing cells were placed in a growth medium containing 1% of its usual iron. The cultures were then sampled periodically for 10 days and prepared for thin sectioning TEM to assess the effects of iron limitation.

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