scholarly journals HuGoS: a virtual environment for studying collective human behavior from a swarm intelligence perspective

2021 ◽  
Author(s):  
Nicolas Coucke ◽  
Mary Katherine Heinrich ◽  
Axel Cleeremans ◽  
Marco Dorigo
Keyword(s):  
Swarm Intelligence ◽  
Virtual Environment ◽  
Open Source Software ◽  
Collective Behavior ◽  
Self Organization ◽  
Game Development ◽  
Development Platform ◽  
Self Organized ◽  
Intelligence Studies ◽  
Human Participants

AbstractSwarm intelligence studies self-organized collective behavior resulting from interactions between individuals, typically in animals and artificial agents. Some studies from cognitive science have also demonstrated self-organization mechanisms in humans, often in pairs. Further research into the topic of human swarm intelligence could provide a better understanding of new behaviors and larger human collectives. This requires studies with multiple human participants in controlled experiments in a wide variety of scenarios, where a rich scope of possible interactions can be isolated and captured. In this paper, we present HuGoS—‘Humans Go Swarming’—a multi-user virtual environment implemented using the Unity game development platform, as a comprehensive tool for experimentation in human swarm intelligence. We demonstrate the functionality of HuGoS with naïve participants in a browser-based implementation, in a coordination task involving collective decision-making, messaging and signaling, and stigmergy. By making HuGoS available as open-source software, we hope to facilitate further research in the field of human swarm intelligence.

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 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.

scholarly journals Swarm Intelligence for Self-Organized Clustering (Extended Abstract)

2020 ◽  
Author(s):  
Michael C. Thrun ◽  
Alfred Ultsch
Keyword(s):  
Swarm Intelligence ◽  
Data Visualization ◽  
High Dimensional Data ◽  
Self Organization ◽  
High Dimensional ◽  
Topographic Map ◽  
Visualization Technique ◽  
Robust Clustering ◽  
Related Data ◽  
Self Organized

The Databionic swarm (DBS) is a flexible and robust clustering framework that consists of three independent modules: swarm based projection, high-dimensional data visualization and representation guided clustering. The first module is the parameter-free projection method Pswarm, which exploits concepts of self-organization and emergence, game theory, and swarm intelligence. The second module is a parameter-free high-dimensional data visualization technique called topographic map. It uses the generalized U-matrix, which enables to estimate first, if any cluster tendency exists and second, the estimation of the number of clusters. The third module offers a clustering method which can be verified by the visualization and vice versa. Benchmarking w.r.t. conventional algorithms demonstrated that DBS can outperform them. Several applications showed that cluster structures provided by DBS are meaningful. Exemplary, a clustering of worldwide country-related data w.r.t the COVID-19 pandemic is presented here. Code and data is made available via open source.

scholarly journals Mutual anticipation can contribute to self-organization in human crowds

2020 ◽  
Author(s):  
Hisashi Murakami ◽  
Claudio Feliciani ◽  
Yuta Nishiyama ◽  
Katsuhiro Nishinari
Keyword(s):  
Collective Behavior ◽  
Movement Pattern ◽  
Self Organization ◽  
Scale Free ◽  
Crowd Management ◽  
Self Organized ◽  
Seeking Behavior ◽  
Physical Particle ◽  
Lane Formation ◽  
Walking Speeds

AbstractHuman crowds provide paradigmatic examples of collective behavior emerging through self-organization. Although the underlying interaction has been considered to obey the distance-dependent law, resembling physical particle systems, recent findings emphasized that pedestrian motions are fundamentally influenced by the anticipated future positions of their neighbors rather than their current positions. Therefore, anticipatory interaction may play a crucial role in collective patterning. However, whether and how individual anticipation functionally benefits the group is not well-understood. We suggest that collective patterning in human crowds is promoted by anticipatory path-seeking behavior resulting in a scale-free movement pattern, called the Lévy walk. In our experiments of lane formation, a striking example of self-organized patterning in human crowds where people moving in opposite directions spontaneously segregate into several unidirectional lanes, we manipulated some pedestrians’ ability to anticipate by having them type on a mobile phone while walking. The manipulation slowed overall walking speeds and delayed the onset of global patterning, and the distracted pedestrians sometimes failed to achieve their usual walking strategy. Moreover, we observed that the delay of global patterning depends on decisions made by pedestrians who were moving toward the distracted ones and had no choice but to take sudden large steps, presumably because of difficulty in anticipating the motions of their counterparts. These results imply that mutual anticipation between pedestrians facilitates efficient transition to emergent patterning in situations where nobody within a crowd is distracted. Our findings may contribute to efficient crowd management and inform future models of self-organizing systems.

scholarly journals Self-replication of a quantum artificial organism driven by single-photon pulses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniel Valente
Keyword(s):  
Self Assembly ◽  
Artificial Life ◽  
Single Photon ◽  
Self Organization ◽  
Physical Systems ◽  
Self Organized ◽  
Living Organisms ◽  
A Chain ◽  
Thermodynamic Mechanism ◽  
Self Replication

AbstractImitating the transition from inanimate to living matter is a longstanding challenge. Artificial life has achieved computer programs that self-replicate, mutate, compete and evolve, but lacks self-organized hardwares akin to the self-assembly of the first living cells. Nonequilibrium thermodynamics has achieved lifelike self-organization in diverse physical systems, but has not yet met the open-ended evolution of living organisms. Here, I look for the emergence of an artificial-life code in a nonequilibrium physical system undergoing self-organization. I devise a toy model where the onset of self-replication of a quantum artificial organism (a chain of lambda systems) is owing to single-photon pulses added to a zero-temperature environment. I find that spontaneous mutations during self-replication are unavoidable in this model, due to rare but finite absorption of off-resonant photons. I also show that the replication probability is proportional to the absorbed work from the photon, thereby fulfilling a dissipative adaptation (a thermodynamic mechanism underlying lifelike self-organization). These results hint at self-replication as the scenario where dissipative adaptation (pointing towards convergence) coexists with open-ended evolution (pointing towards divergence).

scholarly journals Travelling colourful patterns in self-organized cellulose-based liquid crystalline structures

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Pedro E. S. Silva ◽  
Ricardo Chagas ◽  
Susete N. Fernandes ◽  
Pawel Pieranski ◽  
Robin L. B. Selinger ◽  
...  
Keyword(s):  
Simple Model ◽  
Temporal Variation ◽  
Liquid Crystalline ◽  
Diffusion Mechanism ◽  
Reaction Diffusion ◽  
Self Organization ◽  
Spatial And Temporal Variation ◽  
Living Matter ◽  
Equilibrium Conditions ◽  
Self Organized

AbstractCellulose-based systems are useful for many applications. However, the issue of self-organization under non-equilibrium conditions, which is ubiquitous in living matter, has scarcely been addressed in cellulose-based materials. Here, we show that quasi-2D preparations of a lyotropic cellulose-based cholesteric mesophase display travelling colourful patterns, which are generated by a chemical reaction-diffusion mechanism being simultaneous with the evaporation of solvents at the boundaries. These patterns involve spatial and temporal variation in the amplitude and sign of the helix´s pitch. We propose a simple model, based on a reaction-diffusion mechanism, which simulates the observed spatiotemporal colour behaviour.

scholarly journals Self-Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Andrey Dmitriev ◽  
Victor Dmitriev ◽  
Stepan Balybin
Keyword(s):  
Time Series ◽  
Critical State ◽  
Empirical Investigation ◽  
Phenomenological Theory ◽  
Self Organization ◽  
Protest Movements ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Stochastic Sources ◽  
Adiabatic Mode

Recently, there has been an increasing number of empirical evidence supporting the hypothesis that spread of avalanches of microposts on social networks, such as Twitter, is associated with some sociopolitical events. Typical examples of such events are political elections and protest movements. Inspired by this phenomenon, we built a phenomenological model that describes Twitter’s self-organization in a critical state. An external manifestation of this condition is the spread of avalanches of microposts on the network. The model is based on a fractional three-parameter self-organization scheme with stochastic sources. It is shown that the adiabatic mode of self-organization in a critical state is determined by the intensive coordinated action of a relatively small number of network users. To identify the critical states of the network and to verify the model, we have proposed a spectrum of three scaling indicators of the observed time series of microposts.

scholarly journals Topology assisted self-organization of colloidal nanoparticles: application to 2D large-scale nanomastering

2014 ◽  
Vol 5 ◽  
pp. 1203-1209 ◽  
Author(s):  
Hind Kadiri ◽  
Serguei Kostcheev ◽  
Daniel Turover ◽  
Rafael Salas-Montiel ◽  
Komla Nomenyo ◽  
...  
Keyword(s):  
Large Scale ◽  
The Self ◽  
Surface Topology ◽  
Self Organization ◽  
Hydrogen Silsesquioxane ◽  
Polystyrene Beads ◽  
Structure Topology ◽  
Self Organized ◽  
Novel Method ◽  
Long Range Ordering

Our aim was to elaborate a novel method for fully controllable large-scale nanopatterning. We investigated the influence of the surface topology, i.e., a pre-pattern of hydrogen silsesquioxane (HSQ) posts, on the self-organization of polystyrene beads (PS) dispersed over a large surface. Depending on the post size and spacing, long-range ordering of self-organized polystyrene beads is observed wherein guide posts were used leading to single crystal structure. Topology assisted self-organization has proved to be one of the solutions to obtain large-scale ordering. Besides post size and spacing, the colloidal concentration and the nature of solvent were found to have a significant effect on the self-organization of the PS beads. Scanning electron microscope and associated Fourier transform analysis were used to characterize the morphology of the ordered surfaces. Finally, the production of silicon molds is demonstrated by using the beads as a template for dry etching.

scholarly journals Geometric Effect for Biological Reactors and Biological Fluids

2018 ◽  
Vol 5 (4) ◽  
pp. 110 ◽  
Author(s):  
Kazusa Beppu ◽  
Ziane Izri ◽  
Yusuke Maeda ◽  
Ryota Sakamoto
Keyword(s):  
Biological Fluids ◽  
Biological Systems ◽  
Self Organization ◽  
Active Matter ◽  
Confined Space ◽  
Self Organized ◽  
Motile Cells ◽  
Recent Developments ◽  
A Cell

As expressed “God made the bulk; the surface was invented by the devil” by W. Pauli, the surface has remarkable properties because broken symmetry in surface alters the material properties. In biological systems, the smallest functional and structural unit, which has a functional bulk space enclosed by a thin interface, is a cell. Cells contain inner cytosolic soup in which genetic information stored in DNA can be expressed through transcription (TX) and translation (TL). The exploration of cell-sized confinement has been recently investigated by using micron-scale droplets and microfluidic devices. In the first part of this review article, we describe recent developments of cell-free bioreactors where bacterial TX-TL machinery and DNA are encapsulated in these cell-sized compartments. Since synthetic biology and microfluidics meet toward the bottom-up assembly of cell-free bioreactors, the interplay between cellular geometry and TX-TL advances better control of biological structure and dynamics in vitro system. Furthermore, biological systems that show self-organization in confined space are not limited to a single cell, but are also involved in the collective behavior of motile cells, named active matter. In the second part, we describe recent studies where collectively ordered patterns of active matter, from bacterial suspensions to active cytoskeleton, are self-organized. Since geometry and topology are vital concepts to understand the ordered phase of active matter, a microfluidic device with designed compartments allows one to explore geometric principles behind self-organization across the molecular scale to cellular scale. Finally, we discuss the future perspectives of a microfluidic approach to explore the further understanding of biological systems from geometric and topological aspects.

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