scholarly journals Scale-Free Features in Collective Robot Foraging

2019 ◽  
Vol 9 (13) ◽  
pp. 2667 ◽  
Author(s):  
Ilja Rausch ◽  
Yara Khaluf ◽  
Pieter Simoens
Keyword(s):  
Resting State ◽  
Information Exchange ◽  
Large Scale ◽  
Complex Task ◽  
Characteristic Scale ◽  
Strong Correlations ◽  
Scale Free ◽  
Robot Swarms ◽  
Communication Links ◽  
Collective Foraging

In many complex systems observed in nature, properties such as scalability, adaptivity, or rapid information exchange are often accompanied by the presence of features that are scale-free, i.e., that have no characteristic scale. Following this observation, we investigate the existence of scale-free features in artificial collective systems using simulated robot swarms. We implement a large-scale swarm performing the complex task of collective foraging, and demonstrate that several space and time features of the simulated swarm—such as number of communication links or time spent in resting state—spontaneously approach the scale-free property with moderate to strong statistical plausibility. Furthermore, we report strong correlations between the latter observation and swarm performance in terms of the number of retrieved items.

scholarly journals When less is more: Robot swarms adapt better to changes with constrained communication

2021 ◽  
Vol 6 (56) ◽  
pp. eabf1416
Author(s):  
Mohamed S. Talamali ◽  
Arindam Saha ◽  
James A. R. Marshall ◽  
Andreagiovanni Reina
Keyword(s):  
Information Exchange ◽  
Mean Field ◽  
Voter Model ◽  
Communication Range ◽  
Less Is More ◽  
Robot Swarm ◽  
Swarm Dynamics ◽  
Robot Swarms ◽  
Communication Links ◽  
The Individual

To effectively perform collective monitoring of dynamic environments, a robot swarm needs to adapt to changes by processing the latest information and discarding outdated beliefs. We show that in a swarm composed of robots relying on local sensing, adaptation is better achieved if the robots have a shorter rather than longer communication range. This result is in contrast with the widespread belief that more communication links always improve the information exchange on a network. We tasked robots with reaching agreement on the best option currently available in their operating environment. We propose a variety of behaviors composed of reactive rules to process environmental and social information. Our study focuses on simple behaviors based on the voter model—a well-known minimal protocol to regulate social interactions—that can be implemented in minimalistic machines. Although different from each other, all behaviors confirm the general result: The ability of the swarm to adapt improves when robots have fewer communication links. The average number of links per robot reduces when the individual communication range or the robot density decreases. The analysis of the swarm dynamics via mean-field models suggests that our results generalize to other systems based on the voter model. Model predictions are confirmed by results of multiagent simulations and experiments with 50 Kilobot robots. Limiting the communication to a local neighborhood is a cheap decentralized solution to allow robot swarms to adapt to previously unknown information that is locally observed by a minority of the robots.

scholarly journals Robustness of Internet of Battlefield Things (IoBT): A Directed Network Perspective

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1166
Author(s):  
Yuan Feng ◽  
Menglin Li ◽  
Chengyi Zeng ◽  
Hongfu Liu
Keyword(s):  
Real Time ◽  
Situation Awareness ◽  
Information Exchange ◽  
Large Scale ◽  
Network Connectivity ◽  
The Internet ◽  
Directed Network ◽  
Communication Link ◽  
Attack Behavior ◽  
Communication Links

Through the combination of various intelligent devices and the Internet to form a large-scale network, the Internet of Things (IoT) realizes real-time information exchange and communication between devices. IoT technology is expected to play an essential role in improving the combat effectiveness and situation awareness ability of armies. The interconnection between combat equipment and other battlefield resources is referred to as the Internet of Battlefield Things (IoBT). Battlefield real-time data sharing and the cooperative decision-making among commanders are highly dependent on the connectivity between different combat units in the network. However, due to the wireless characteristics of communication, a large number of communication links are directly exposed in the complex battlefield environment, and various cyber or physical attacks threaten network connectivity. Therefore, the ability to maintain network connectivity under adversary attacks is a critical property for the IoBT. In this work, we propose a directed network model and connectivity measurement of the IoBT network. Then, we develop an optimal attack strategy optimization model to simulate the optimal attack behavior of the enemy. By comparing with the disintegration effect of some benchmark strategies, we verify the optimality of the model solution and find that the robustness of the IoBT network decreases rapidly with an increase of the unidirectional communication links in the network. The results show that the adversary will change the attack mode according to the parameter settings of attack resources and network communication link density. In order to enhance the network robustness, we need to adjust the defense strategy in time to deal with this change. Finally, we validated the model and theoretical analysis proposed in this paper through experiments on a real military network.

scholarly journals Dynamic relationships between spontaneous and evoked electrophysiological activity

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Soren Wainio-Theberge ◽  
Annemarie Wolff ◽  
Georg Northoff
Keyword(s):  
Neural Activity ◽  
Large Scale ◽  
Behavioral Outcomes ◽  
Low Frequencies ◽  
Scale Free ◽  
Non Invasive ◽  
Spontaneous Neural Activity ◽  
Electrophysiological Signals ◽  
Evoked Activity ◽  
Dynamic Relationships

AbstractSpontaneous neural activity fluctuations have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioral outcomes. However, the complex electrophysiological mechanisms by which these fluctuations shape stimulus-evoked neural activity remain largely to be explored. Employing a large-scale magnetoencephalographic dataset and an electroencephalographic replication dataset, we investigate the relationship between spontaneous and evoked neural activity across a range of electrophysiological variables. We observe that for high-frequency activity, high pre-stimulus amplitudes lead to greater evoked desynchronization, while for low frequencies, high pre-stimulus amplitudes induce larger degrees of event-related synchronization. We further decompose electrophysiological power into oscillatory and scale-free components, demonstrating different patterns of spontaneous-evoked correlation for each component. Finally, we find correlations between spontaneous and evoked time-domain electrophysiological signals. Overall, we demonstrate that the dynamics of multiple electrophysiological variables exhibit distinct relationships between their spontaneous and evoked activity, a result which carries implications for experimental design and analysis in non-invasive electrophysiology.

scholarly journals Internet of Vehicles: Commencing Intellectual Hoarse Towards Self-Regulating Cars and Vehicular Clouds for Smart Transportation Structure [Vehicular Ad-Hoc Network: A Review and Application in the Internet of Vehicles]

2018 ◽  
Vol 7 (3.12) ◽  
pp. 545
Author(s):  
Risabh Mishra ◽  
M Safa ◽  
Aditya Anand
Keyword(s):  
Internet Of Things ◽  
Wireless Communication ◽  
Automobile Industry ◽  
Information Exchange ◽  
Large Scale ◽  
Intelligent Transportation System ◽  
Information Service ◽  
The Internet ◽  
Internet Of Vehicles ◽  
The Internet Of Things

Recent advances in wireless communication technologies and automobile industry have triggered a significant research interest in the field of Internet of Vehicles over the past few years.The advanced period of the Internet of Things is guiding the development of conventional Vehicular Networks to the Internet of Vehicles.In the days of Internet connectivity there is need to be in safe and problem-free environment.The Internet of Vehicles (IoV) is normally a mixing of three networks: an inter-vehicleNetwork, an intra-vehicle network, and a vehicle to vehicle network.Based on  idea of three networks combining into one, we define  Internet of Vehicles as a large-scale distributed system to wireless communication and information exchange between vehicle2X (X: vehicle, road, human and internet).It is a combined   network for supporting intelligent traffic management, intelligent dynamic information service, and intelligent vehicle control, representation of an application of the Internet of Things (IoT) technology for intelligent transportation system (ITS).  

Advanced CFD Simulations of free-surface flows around modern sailing yachts using a newly developed openFOAM solver

2016 ◽  
Author(s):  
Janek Meyer ◽  
Hannes Renzsch ◽  
Kai Graf ◽  
Thomas Slawig
Keyword(s):  
Free Surface ◽  
Large Scale ◽  
Breaking Waves ◽  
Free Surface Flows ◽  
Body Motion ◽  
Computational Time ◽  
Efficient Computation ◽  
Surface Flows ◽  
Scale Free ◽  
Wide Range

While plain vanilla OpenFOAM has strong capabilities with regards to quite a few typical CFD-tasks, some problems actually require additional bespoke solvers and numerics for efficient computation of high-quality results. One of the fields requiring these additions is the computation of large-scale free-surface flows as found e.g. in naval architecture. This holds especially for the flow around typical modern yacht hulls, often planing, sometimes with surface-piercing appendages. Particular challenges include, but are not limited to, breaking waves, sharpness of interface, numerical ventilation (aka streaking) and a wide range of flow phenomenon scales. A new OF-based application including newly implemented discretization schemes, gradient computation and rigid body motion computation is described. In the following the new code will be validated against published experimental data; the effect on accuracy, computational time and solver stability will be shown by comparison to standard OF-solvers (interFoam / interDyMFoam) and Star CCM+. The code’s capabilities to simulate complex “real-world” flows are shown on a well-known racing yacht design.

scholarly journals Small-scale characteristics of extremely high latitude aurora

2009 ◽  
Vol 27 (9) ◽  
pp. 3335-3347 ◽  
Author(s):  
J. A. Cumnock ◽  
L. G. Blomberg ◽  
A. Kullen ◽  
T. Karlsson ◽  
Keyword(s):  
High Latitude ◽  
Large Scale ◽  
Small Scale ◽  
Strong Correlations ◽  
Polar Cap ◽  
Plasma Flows ◽  
Ionospheric Convection ◽  
Local Closure ◽  
Scale Characteristics

Abstract. We examine 14 cases of an interesting type of extremely high latitude aurora as identified in the precipitating particles measured by the DMSP F13 satellite. In particular we investigate structures within large-scale arcs for which the particle signatures are made up of a group of multiple distinct thin arcs. These cases are chosen without regard to IMF orientation and are part of a group of 87 events where DMSP F13 SSJ/4 measures emissions which occur near the noon-midnight meridian and are spatially separated from both the dawnside and duskside auroral ovals by wide regions with precipitating particles typical of the polar cap. For 73 of these events the high-latitude aurora consists of a continuous region of precipitating particles. We focus on the remaining 14 of these events where the particle signatures show multiple distinct thin arcs. These events occur during northward or weakly southward IMF conditions and follow a change in IMF By. Correlations are seen between the field-aligned currents and plasma flows associated with the arcs, implying local closure of the FACs. Strong correlations are seen only in the sunlit hemisphere. The convection associated with the multiple thin arcs is localized and has little influence on the large-scale convection. This also implies that the sunward flow along the arcs is unrelated to the overall ionospheric convection.

scholarly journals Stroke-related alterations in inter-areal communication revealed via Granger causality analysis

2021 ◽  
Author(s):  
Michele Allegra ◽  
Chiara Favaretto ◽  
Nicholas Metcalf ◽  
Maurizio Corbetta ◽  
Andrea Brovelli
Keyword(s):  
Functional Connectivity ◽  
Granger Causality ◽  
Resting State ◽  
Information Transfer ◽  
Large Scale ◽  
Functional Organization ◽  
Information Flows ◽  
Causality Analysis ◽  
Stroke Patients ◽  
Granger Causality Analysis

ABSTRACTNeuroimaging and neurological studies suggest that stroke is a brain network syndrome. While causing local ischemia and cell damage at the site of injury, stroke strongly perturbs the functional organization of brain networks at large. Critically, functional connectivity abnormalities parallel both behavioral deficits and functional recovery across different cognitive domains. However, the reasons for such relations remain poorly understood. Here, we tested the hypothesis that alterations in inter-areal communication underlie stroke-related modulations in functional connectivity (FC). To this aim, we used resting-state fMRI and Granger causality analysis to quantify information transfer between brain areas and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was strongly decreased with respect to healthy controls. Second, information transfer within the affected hemisphere, and from the affected to the intact hemisphere was reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they were correlated with impaired performance in several behavioral domains. Overall, our results support the hypothesis that stroke perturbs inter-areal communication within and across hemispheres, and suggest novel therapeutic approaches aimed at restoring normal information flow.SIGNIFICANCE STATEMENTA thorough understanding of how stroke perturbs brain function is needed to improve recovery from the severe neurological syndromes affecting stroke patients. Previous resting-state neuroimaging studies suggested that interaction between hemispheres decreases after stroke, while interaction between areas of the same hemisphere increases. Here, we used Granger causality to reconstruct information flows in the brain at rest, and analyze how stroke perturbs them. We showed that stroke causes a global reduction of inter-hemispheric communication, and an imbalance between the intact and the affected hemisphere: information flows within and from the latter are impaired. Our results may inform the design of stimulation therapies to restore the functional balance lost after stroke.

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