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A Survey Paper on Particle Swarm Optimization based Routing Protocols in Mobile Ad-Hoc Networks

Shruti Dixit, Rakesh Singhai
2015 International Journal of Computer Applications  
The purpose of the research is to apply swarm intelligence on routing algorithms used in MANET.  ...  They are characterized by a decentralized way of working that mimics the behaviour of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with complex problems.  ...  SWARM INTELLIGENCE Swarm Intelligence (SI) is mainly defined as the behaviour of natural or artificial self-organized, decentralized systems.  ... 
doi:10.5120/21100-3812 fatcat:rmuc46q6unhl5kvpgduambywu4

Swarm Intelligence for Urban Dynamics Modelling

Rawan Ghnemat, Cyrille Bertelle, Gérard H. E. Duchamp, Barna Laszlo Iantovics, Enachescu Calin, Florin Gheorghe Filip
2009 AIP Conference Proceedings  
We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions.  ...  In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence.  ...  An algorithm based on the usage of pheromon template is proposed as an extension of this self-organization process, allowing to control some spatial constraints during the self-organization phenomenon.  ... 
doi:10.1063/1.3130612 fatcat:gljkalw3rvaj7lkhb5vczhnlue

Agent-based modeling using swarm intelligence in geographical information systems

Rawan Ghnemat, Cyrille Bertelle, Gerard H.E. Duchamp
2008 2008 International Conference on Innovations in Information Technology  
Combination of decentralized approaches based on emergent clustering mixed with spatial multi criteria constraints or attractions developed , extension of termite nest building algorithms has been proposed  ...  In this paper swarm intelligence algorithms are presented to deal with dynamical and spatial Organization emergence.  ...  Schweitzer proposes also a generic method based on distributed agents, using approaches of statistical many-particle physics [9] .  ... 
doi:10.1109/innovations.2008.4781737 fatcat:ghhigcugwrcs7p6uu4c7ttjjiu

6x9=42 | A brief introduction to swarm intelligence [article]

H. Kemal Ilter
2019 Figshare  
Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial.  ...  Introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic system.  ...  "A modified particle swarm optimizer". Proceedings of IEEE International Conference on Evolutionary Computation. pp. 69-73. • Kennedy, J. (1997). "The particle swarm: social adapta-• M.  ... 
doi:10.6084/m9.figshare.10193084.v1 fatcat:dazq3r2m45bmpm7ovs4xvfwsoi

USING SWARM APPROACHES FOR STUDENT SELECTION PROCESS

Reetika Nagar .
2014 International Journal of Research in Engineering and Technology  
of simple agents or particles.  ...  In this paper, introduction of swarm intelligence, its variants ant colony optimization and particle swarm optimization, and student selection process has been given.  ...  INTRODUCTION Swarm intelligence (SI) focuses on the study of the collective behaviour of self-organized and decentralized systems, natural or artificial systems to solve complex problems [1] .  ... 
doi:10.15623/ijret.2014.0312002 fatcat:jrsqfhjl6zdajlzzbu2crpyi7y

Swarm-Based Morphogenetic Artificial Life [chapter]

Hiroki Sayama
2012 Understanding Complex Systems  
We present a swarm-based framework for designing and implementing morphogenetic artifacts that can grow, self-organize and self-repair in a fully decentralized manner.  ...  The proposed framework is based on our earlier work, Swarm Chemistry, a computational model of particle swarms where mobile particles with different kinetic properties interact with each other to produce  ...  Second, the self-organizing patterns produced in our framework moderately depends on the size of the swarm.  ... 
doi:10.1007/978-3-642-33902-8_8 fatcat:fj5mhxhk4bd5tocnfia4hzmtre

Nature-Inspired Swarm Intelligence and Its Applications

Sangita Roy, Samir Biswas, Sheli Sinha Chaudhuri
2014 International Journal of Modern Education and Computer Science  
In this paper the existing research works are analysed to show the behavior in social insects by using self-organization, positive feedback, negative feedback, amplification of fluctuation, multiple interactions  ...  Finally authors focus on swarm robots applications in telecommunication fields, civil engineering and digital image processing. mode of behavior every time the environment changes.5.  ...  Swarm-based robotics is distributed, robust, decentralized and self-organized. Sometimes a single robot is unable to perform a complete task alone due to its complexity and time consumption.  ... 
doi:10.5815/ijmecs.2014.12.08 fatcat:u5tfnsvaonhwtbvtgsqii2hnce

Preface

Ying Tan, Yuhui Shi, Xin Yao
2016 Natural Computing  
As a branch of meta-heuristic algorithms, swarm intelligence is concerned with the collective behavior of decentralized, self-organized and populated systems.  ...  One of the most popular swarm intelligence algorithm is the Particle Swarm Optimization (PSO), which is inspired by the social behavior of bird flocking and has been widely used in real-parameter optimization  ...  As a branch of meta-heuristic algorithms, swarm intelligence is concerned with the collective behavior of decentralized, self-organized and populated systems.  ... 
doi:10.1007/s11047-016-9594-x fatcat:33bcelseujffheoypz4pdaskay

Editorial: Special issue on advances in swarm intelligence for neural networks

Ying Tan
2015 Neurocomputing  
As usual, SI systems are primarily inspired by natural systems and greatly depend on certain key principles such as decentralization, stigmergy, collaboration, and self-organization which are observed  ...  Besides the researches on theoretical analysis and algorithms, extensive application researches of SI have also been carried out, in particular, the swarm intelligence for neural networks.  ...  Four papers of researches on swarm robot systems and multi agent systems are included in the third group.  ... 
doi:10.1016/j.neucom.2013.10.045 fatcat:qea3n7wdzrbedh7vtrgta2kwie

Swarm Robotics: A Perspective on the Latest Reviewed Concepts and Applications

Pollyanna G. Faria Dias, Mateus C. Silva, Geraldo P. Rocha Rocha Filho, Patrícia A. Vargas, Luciano P. Cota, Gustavo Pessin
2021 Sensors  
Known as an artificial intelligence subarea, Swarm Robotics is a developing study field investigating bio-inspired collaborative control approaches and integrates a huge collection of agents, reasonably  ...  plain robots, in a distributed and decentralized manner.  ...  The swarm is decentralized, self-organized, and distributed [27] [28] [29] [30] [31] [32] . 6.  ... 
doi:10.3390/s21062062 pmid:33804187 pmcid:PMC8000604 fatcat:3noeec6llvh43pklgdttvkcmme

Particle Swarm Optimization for Load Balancing in Distributed Computing Systems – A Survey

Vidya S. Handur, Et. al.
2021 Turkish Journal of Computer and Mathematics Education  
The paper aims at the study of how Particle Swarm Optimization approach is used to achieve an optimal solution for load balancing in distributed computing system.  ...  Load balancing has been one of the concerns in the distributed computing systems where the computing nodes do not have a global view of the network.  ...  Properties of SI are: • It is an Agent Based Model • Agents interact locally with each other to exhibit global behavior • Agents are self-organizedAgents follow simple rules • Agents are very adaptive  ... 
doi:10.17762/turcomat.v12i1s.1766 fatcat:urlrc5fb4nfcpossklfq7i5ihq

A Deep Reinforcement Learning Environment for Particle Robot Navigation and Object Manipulation [article]

Jeremy Shen, Erdong Xiao, Yuchen Liu, Chen Feng
2022 arXiv   pre-print
However, the particle robot system presents a new set of challenges for DRL differing from existing swarm robotics systems: the low degrees of freedom of each robot and the increased necessity of coordination  ...  Further development of DRL algorithms is necessary in order to accomplish the proposed tasks.  ...  Although the superagent assumption is still a challenging task, we plan on benchmarking the environment in a decentralized multi-agent setting in order to fully extract the advantages of a low-level swarm  ... 
arXiv:2203.06464v1 fatcat:hyto64ijf5fr3f3njjwbddxu2a

Stochastic Metaheuristics as Sampling Techniques using Swarm Intelligence [chapter]

Johann Dreo, Patrick Siarry
2007 Swarm Intelligence, Focus on Ant and Particle Swarm Optimization  
In the metaheuristics field, swarm intelligence was so explicitely used on two main fronts: via an approach "self-organized systems" (having given place to ant colony algorithms) and via an approach "socio-cognitive  ...  systems" (having led to the particle swarm optimization).  ...  Self-organization and swarm intelligence As a field of research, swarm intelligence deals with the study of self-organization in natural and artificial swarm systems.  ... 
doi:10.5772/5105 fatcat:w3yk4piys5dtrowxnr4pt6b6qi

Engineering Swarming Systems [chapter]

H. Van Dyke Parunak, Sven A. Brueckner
2004 Methodologies and Software Engineering for Agent Systems  
This paper defines swarming and the concepts of self-organization and emergence that underlie it.  ...  Military historians focus less on the process of self-organization and more on the resulting organization itself: "the systematic pulsing of force and/or fire by dispersed, internetted units, so as to  ...  State-of-the-art algorithms of this sort are based not on design, but on selection.  ... 
doi:10.1007/1-4020-8058-1_21 fatcat:cktj5vuoizaldghvykgs3bstta

Adversarial Impacts on Autonomous Decentralized Lightweight Swarms [article]

Shaya Wolf, Rafer Cooley, Mike Borowczak
2020 arXiv   pre-print
Some drones rely on decentralized protocols that exhibit emergent behavior across the swarm.  ...  The adversarial swarm in this work utilizes an attack vector embedded within the decentralized movement algorithm of a previously defined autonomous swarm designed to create a perimeter sentry swarm.  ...  of the SHARKS swarm.  ... 
arXiv:2002.09109v1 fatcat:2ntjziq5erdlvhbmjbltxv5eza
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