Emergence and dynamics of unconfined self-organized vortices in active magnetic roller liquids

Soft Matter ◽  
2021 ◽  
Author(s):  
Koohee Han ◽  
Andreas Glatz ◽  
Alexey Snezhko
Keyword(s):  
Collective Behavior ◽  
Living Systems ◽  
Equilibrium Dynamics ◽  
Self Organized ◽  
Macroscopic States

Actively driven colloids demonstrate complex out-of-equilibrium dynamics often rivaling self-organized patterns and collective behavior observed in living systems. Recent studies revealed the emergence of steady macroscopic states with multiple interacting...

scholarly journals On the Complexities of Complex Economic Dynamics

1999 ◽  
Vol 13 (4) ◽  
pp. 169-192 ◽  
Author(s):  
J. Barkley Rosser
Keyword(s):  
Adaptive Learning ◽  
Rational Expectations ◽  
Interacting Particle Systems ◽  
Complexity Analysis ◽  
Evolutionary Game ◽  
Equilibrium Dynamics ◽  
Self Organized ◽  
Policy Debates ◽  
Interacting Particle ◽  
Self Organized Criticality

Complex economic nonlinear dynamics endogenously do not converge to a point, a limit cycle, or an explosion. Their study developed out of earlier studies of cybernetic, catastrophic, and chaotic systems. Complexity analysis stresses interactions among dispersed agents without a global controller, tangled hierarchies, adaptive learning, evolution, and novelty, and out-of-equilibrium dynamics. Complexity methods include interacting particle systems, self-organized criticality, and evolutionary game theory, to simulate artificial stock markets and other phenomena. Theoretically, bounded rationality replaces rational expectations. Complexity theory influences empirical methods and restructures policy debates.

Comment on “Self-organized criticality in living systems” by C. Adami

1997 ◽  
Vol 228 (3) ◽  
pp. 202-204 ◽  
Author(s):  
M.E.J. Newman ◽  
Simon M. Fraser ◽  
Kim Sneppen ◽  
William A. Tozier
Keyword(s):  
Living Systems ◽  
Self Organized ◽  
Self Organized Criticality

CAN COMPLEX CELLULAR PROCESSES BE GOVERNED BY SIMPLE LINEAR RULES?

2009 ◽  
Vol 07 (01) ◽  
pp. 243-268 ◽  
Author(s):  
KUMAR SELVARAJOO ◽  
MASARU TOMITA ◽  
MASA TSUCHIYA
Keyword(s):  
Biological Networks ◽  
Biological Network ◽  
Living Systems ◽  
Regulatory Motifs ◽  
Cellular Processes ◽  
Self Organized ◽  
Wide Range ◽  
Activation Response ◽  
Physical Reasons

Complex living systems have shown remarkably well-orchestrated, self-organized, robust, and stable behavior under a wide range of perturbations. However, despite the recent generation of high-throughput experimental datasets, basic cellular processes such as division, differentiation, and apoptosis still remain elusive. One of the key reasons is the lack of understanding of the governing principles of complex living systems. Here, we have reviewed the success of perturbation–response approaches, where without the requirement of detailed in vivo physiological parameters, the analysis of temporal concentration or activation response unravels biological network features such as causal relationships of reactant species, regulatory motifs, etc. Our review shows that simple linear rules govern the response behavior of biological networks in an ensemble of cells. It is daunting to know why such simplicity could hold in a complex heterogeneous environment. Provided physical reasons can be explained for these phenomena, major advancement in the understanding of basic cellular processes could be achieved.

scholarly journals AN EXPERIMENTAL COLLECTIVE INTELLIGENCE RESEARCH TOOL

2014 ◽  
pp. 40-50
Author(s):  
Bei Wang ◽  
Dung Hoang ◽  
Idris Daiz ◽  
Chiedu Okpala ◽  
Tarek M. Sobh
Keyword(s):  
Collective Behavior ◽  
Collective Intelligence ◽  
Research Tool ◽  
Research Implementation ◽  
Self Organized ◽  
Experimental Software ◽  
Efficient Alternative ◽  
Building Behavior ◽  
Alternative Research ◽  
Software And Hardware

The Collective Intelligence Research Tool (CIRT) is an experimental software and hardware research tool. It provides an inexpensive and efficient alternative research implementation that demonstrates simulations of the collective behavior of self-organized systems, primarily social insects. The software focuses on 2D simulations of the woodchip-collecting behavior of termites and 3D simulations of the building behavior of wasps. The hardware simulation employs a Boe-Bot robot, which has the potential of simulating simple movements of a social insect, by extending its functionality through adding sensors and integrating a control chip.

scholarly journals Parallelized Swarm Intelligence Approach for Solving TSP and JSSP Problems

Algorithms ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 142
Author(s):  
Piotr Jedrzejowicz ◽  
Izabela Wierzbowska
Keyword(s):  
Swarm Intelligence ◽  
Collective Behavior ◽  
Special Class ◽  
Computational Experiment ◽  
Optimization Problems ◽  
Population Based ◽  
Apache Spark ◽  
Self Organized ◽  
Intelligence Approach

One of the possible approaches to solving difficult optimization problems is applying population-based metaheuristics. Among such metaheuristics, there is a special class where searching for the best solution is based on the collective behavior of decentralized, self-organized agents. This study proposes an approach in which a swarm of agents tries to improve solutions from the population of solutions. The process is carried out in parallel threads. The proposed algorithm—based on the mushroom-picking metaphor—was implemented using Scala in an Apache Spark environment. An extended computational experiment shows how introducing a combination of simple optimization agents and increasing the number of threads may improve the results obtained by the model in the case of TSP and JSSP problems.

scholarly journals Higher order interactions in complex networks of phase oscillators promote abrupt synchronization switching

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Per Sebastian Skardal ◽  
Alex Arenas
Keyword(s):  
Simplicial Complex ◽  
Collective Behavior ◽  
Topological Structure ◽  
Higher Order ◽  
Phase Oscillators ◽  
Macroscopic System ◽  
Self Organized ◽  
Pairwise Interactions ◽  
Wide Range ◽  
Rapid Switching

AbstractSynchronization processes play critical roles in the functionality of a wide range of both natural and man-made systems. Recent work in physics and neuroscience highlights the importance of higher-order interactions between dynamical units, i.e., three- and four-way interactions in addition to pairwise interactions, and their role in shaping collective behavior. Here we show that higher-order interactions between coupled phase oscillators, encoded microscopically in a simplicial complex, give rise to added nonlinearity in the macroscopic system dynamics that induces abrupt synchronization transitions via hysteresis and bistability of synchronized and incoherent states. Moreover, these higher-order interactions can stabilize strongly synchronized states even when the pairwise coupling is repulsive. These findings reveal a self-organized phenomenon that may be responsible for the rapid switching to synchronization in many biological and other systems that exhibit synchronization without the need of particular correlation mechanisms between the oscillators and the topological structure.

scholarly journals Emergence of self-organized multivortex states in flocks of active rollers

2020 ◽  
Vol 117 (18) ◽  
pp. 9706-9711 ◽  
Author(s):  
Koohee Han ◽  
Gašper Kokot ◽  
Oleh Tovkach ◽  
Andreas Glatz ◽  
Igor S. Aranson ◽  
...  
Keyword(s):  
Computational Modeling ◽  
Collective Behavior ◽  
Rotational Motion ◽  
Collective Motion ◽  
Self Organization ◽  
Design Strategies ◽  
Vortex Phase ◽  
Active Elements ◽  
Self Organized ◽  
Dynamic Materials

Active matter, both synthetic and biological, demonstrates complex spatiotemporal self-organization and the emergence of collective behavior. A coherent rotational motion, the vortex phase, is of great interest because of its ability to orchestrate well-organized motion of self-propelled particles over large distances. However, its generation without geometrical confinement has been a challenge. Here, we show by experiments and computational modeling that concentrated magnetic rollers self-organize into multivortex states in an unconfined environment. We find that the neighboring vortices more likely occur with the opposite sense of rotation. Our studies provide insights into the mechanism for the emergence of coherent collective motion on the macroscale from the coupling between microscale rotation and translation of individual active elements. These results may stimulate design strategies for self-assembled dynamic materials and microrobotics.

Reinforcement Learning Scheme for Flocking Behavior Emergence

2007 ◽  
Vol 11 (2) ◽  
pp. 155-161 ◽  
Author(s):  
Koichiro Morihiro ◽  
◽  
Teijiro Isokawa ◽  
Haruhiko Nishimura ◽  
Masahito Tomimasu ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Collective Behavior ◽  
A Priori ◽  
The Self ◽  
Self Organized ◽  
Learning Scheme ◽  
Fish Schooling ◽  
Grouping Behavior ◽  
Flocking Behavior ◽  
New Framework

Collective behavior such as bird flocking, land animal herding, and fish schooling is well known in nature. Many observations have shown that there are no leaders to control the behavior of a group. Several models have been proposed for describing the grouping behavior, which we regard as a distinctive example of aggregate motions. In these models, a fixed rule is provided for each of the individuals a priori for their interactions in a reductive and rigid manner. In contrast, we propose a new framework for the self-organized grouping of agents by reinforcement learning. It is important to introduce a learning scheme for causing collective behavior in artificial autonomous distributed systems. The behavior of agents is demonstrated and evaluated through computer simulations and it is shown that their grouping behavior emerges as a result of learning.

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