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Swarm Intelligence

Overview of attention for book
Cover of 'Swarm Intelligence'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 A Particle Swarm Embedding Algorithm for Nonlinear Dimensionality Reduction
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    Chapter 2 ABC-Miner: An Ant-Based Bayesian Classification Algorithm
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    Chapter 3 Analysing Robot Swarm Decision-Making with Bio-PEPA
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    Chapter 4 Automatic Generation of Multi-objective ACO Algorithms for the Bi-objective Knapsack
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    Chapter 5 Bare Bones Particle Swarms with Jumps
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    Chapter 6 Hybrid Algorithms for the Minimum-Weight Rooted Arborescence Problem
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    Chapter 7 Improving the cAnt-MinerPB Classification Algorithm
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    Chapter 8 Introducing Novelty Search in Evolutionary Swarm Robotics
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    Chapter 9 Measuring Diversity in the Cooperative Particle Swarm Optimizer
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    Chapter 10 Multi-armed Bandit Formulation of the Task Partitioning Problem in Swarm Robotics
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    Chapter 11 Scalability Study of Particle Swarm Optimizers in Dynamic Environments
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    Chapter 12 Self-reconfigurable Modular e-pucks
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    Chapter 13 Task Partitioning via Ant Colony Optimization for Distributed Assembly
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    Chapter 14 The Self-adaptive Comprehensive Learning Particle Swarm Optimizer
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    Chapter 15 Towards Swarm Calculus: Universal Properties of Swarm Performance and Collective Decisions
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    Chapter 16 A Hybrid Particle Swarm Optimization Algorithm for the Open Vehicle Routing Problem
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    Chapter 17 A Self-adaptive Heterogeneous PSO Inspired by Ants
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    Chapter 18 A “Thermodynamic” Approach to Multi-robot Cooperative Localization with Noisy Sensors
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    Chapter 19 AcoSeeD: An Ant Colony Optimization for Finding Optimal Spaced Seeds in Biological Sequence Search
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    Chapter 20 Analysis of Ant-Based Routing with Wireless Medium Access Control
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    Chapter 21 Ant-Based Approaches for Solving Autocorrelation Problems
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    Chapter 22 Collision-Induced “Priority Rule” Governs Efficiency of Pheromone-Communicating Swarm Robots
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    Chapter 23 Dynamic Load Balancing Inspired by Cemetery Formation in Ant Colonies
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    Chapter 24 Feasibility of an Ant Colony Optimization Algorithm for Multi-leaf Collimator (MLC) Aperture Definition and Beam Weighting in Volumetric Modulated Arc Therapy (VMAT) Radiotherapy Treatment Planning
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    Chapter 25 Formica ex Machina: Ant Swarm Foraging from Physical to Virtual and Back Again
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    Chapter 26 Improving Peer Review with ACORN: ACO Algorithm for Reviewer’s Network
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    Chapter 27 Learning Finite-State Machines with Ant Colony Optimization
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    Chapter 28 Mobbing Behavior and Deceit and Its Role in Bio-inspired Autonomous Robotic Agents
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    Chapter 29 Performance of Bacterial Foraging Optimization in Dynamic Environments
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    Chapter 30 Piecewise Linear Approximation of n-Dimensional Parametric Curves Using Particle Swarms
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    Chapter 31 Probabilistic Stochastic Diffusion Search
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    Chapter 32 Self-organized Clustering of Square Objects by Multiple Robots
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    Chapter 33 Self-reproduction versus Transition Rules in Ant Colonies for Medical Volume Segmentation
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    Chapter 34 Swarm Interpolation Using an Approximate Chebyshev Distribution
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    Chapter 35 Using MOPSO to Solve Multiobjective Bilevel Linear Problems
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    Chapter 36 Clustering Moodle Data via Ant Colony Optimization
  38. Altmetric Badge
    Chapter 37 Swarm Intelligence
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    Chapter 38 Exploring Different Functions for Heuristics, Discretization, and Rule Quality Evaluation in Ant-Miner
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    Chapter 39 Fuzzy-Based Aggregation with a Mobile Robot Swarm
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    Chapter 40 Maturity of the Particle Swarm as a Metric for Measuring the Particle Swarm Intelligence
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    Chapter 41 Multi-objective Firefly Algorithm for Energy Optimization in Grid Environments
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    Chapter 42 Particle Swarm Optimization with Random Sampling in Variable Neighbourhoods for Solving Global Minimization Problems
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
6 Mendeley
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Title
Swarm Intelligence
Published by
Lecture notes in computer science, January 2012
DOI 10.1007/978-3-642-32650-9
ISBNs
978-3-64-232649-3, 978-3-64-232650-9
Authors

Marco Dorigo, Mauro Birattari, Christian Blum, Anders Lyhne Christensen, Andries P. Engelbrecht, Roderich Groß, Thomas Stützle

Editors

Marco Dorigo, Mauro Birattari, Christian Blum, Anders Lyhne Christensen, Andries P. Engelbrecht, Roderich Groß, Thomas Stützle

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 17%
Unknown 5 83%
Readers by discipline Count As %
Computer Science 1 17%
Unknown 5 83%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 February 2020.
All research outputs
#4,436,713
of 16,650,301 outputs
Outputs from Lecture notes in computer science
#1,835
of 7,711 outputs
Outputs of similar age
#75,151
of 268,667 outputs
Outputs of similar age from Lecture notes in computer science
#22
of 91 outputs
Altmetric has tracked 16,650,301 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,711 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 268,667 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.