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Swarm Intelligence

Overview of attention for book
Cover of 'Swarm Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 A Study on Force-Based Collaboration in Flying Swarms
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    Chapter 2 Automatic Design of Communication-Based Behaviors for Robot Swarms
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    Chapter 3 Behavior Trees as a Control Architecture in the Automatic Modular Design of Robot Swarms
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    Chapter 4 Guidance of Swarms with Agents Having Bearing Only and Limited Visibility Sensors
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    Chapter 5 Hybrid Control of Swarms for Resource Selection
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    Chapter 6 Local Communication Protocols for Learning Complex Swarm Behaviors with Deep Reinforcement Learning
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    Chapter 7 Morphogenesis as a Collective Decision of Agents Competing for Limited Resource: A Plants Approach
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    Chapter 8 Negative Updating Combined with Opinion Pooling in the Best-of-n Problem in Swarm Robotics
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    Chapter 9 On Mimicking the Effects of the Reality Gap with Simulation-Only Experiments
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    Chapter 10 Optimization of Swarm Behavior Assisted by an Automatic Local Proof for a Pattern Formation Task
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    Chapter 11 Quality-Sensitive Foraging by a Robot Swarm Through Virtual Pheromone Trails
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    Chapter 12 Search in a Maze-Like Environment with Ant Algorithms: Complexity, Size and Energy Study
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    Chapter 13 Self-adaptive Quantum Particle Swarm Optimization for Dynamic Environments
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    Chapter 14 Simulating Kilobots Within ARGoS: Models and Experimental Validation
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    Chapter 15 Simulating Multi-robot Construction in ARGoS
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    Chapter 16 Stability Analysis of the Multi-objective Multi-guided Particle Swarm Optimizer
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    Chapter 17 Swarm Attack: A Self-organized Model to Recover from Malicious Communication Manipulation in a Swarm of Simple Simulated Agents
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    Chapter 18 Task-Agnostic Evolution of Diverse Repertoires of Swarm Behaviours
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    Chapter 19 The Best-of-n Problem with Dynamic Site Qualities: Achieving Adaptability with Stubborn Individuals
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    Chapter 20 The Impact of Interaction Models on the Coherence of Collective Decision-Making: A Case Study with Simulated Locusts
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    Chapter 21 The Importance of Component-Wise Stochasticity in Particle Swarm Optimization
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    Chapter 22 The Importance of Information Flow Regulation in Preferentially Foraging Robot Swarms
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    Chapter 23 The Role of Largest Connected Components in Collective Motion
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    Chapter 24 Why the Intelligent Water Drops Cannot Be Considered as a Novel Algorithm
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    Chapter 25 A Cooperative Opposite-Inspired Learning Strategy for Ant-Based Algorithms
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    Chapter 26 A Solution for the Team Selection Problem Using ACO
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    Chapter 27 Boundary Constraint Handling Techniques for Particle Swarm Optimization in High Dimensional Problem Spaces
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    Chapter 28 Does the ACO$$\mathbb {_R}$$ Algorithm Benefit from the Use of Crossover?
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    Chapter 29 Embodied Evolution of Self-organised Aggregation by Cultural Propagation
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    Chapter 30 Experimental Evaluation of ACO for Continuous Domains to Solve Function Optimization Problems
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    Chapter 31 Gaussian-Valued Particle Swarm Optimization
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    Chapter 32 Individual Activity Level and Mobility Patterns of Ants Within Nest Site
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    Chapter 33 Learning Based Leadership in Swarm Navigation
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    Chapter 34 Maintaining Diversity in Robot Swarms with Distributed Embodied Evolution
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    Chapter 35 On Steering Swarms
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    Chapter 36 Vector Field Benchmark for Collective Search in Unknown Dynamic Environments
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Swarm Intelligence
Published by
Springer International Publishing, January 2018
DOI 10.1007/978-3-030-00533-7
978-3-03-000532-0, 978-3-03-000533-7

Marco Dorigo, Mauro Birattari, Christian Blum, Anders L. Christensen, Andreagiovanni Reina, Vito Trianni

Twitter Demographics

The data shown below were collected from the profiles of 18 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 21%
Researcher 4 17%
Student > Doctoral Student 2 8%
Student > Master 2 8%
Professor 2 8%
Other 3 13%
Unknown 6 25%
Readers by discipline Count As %
Computer Science 8 33%
Engineering 6 25%
Agricultural and Biological Sciences 2 8%
Linguistics 1 4%
Unknown 7 29%