With regard to the subject of sensor network node optimization, a strategy for wireless sensor network coverage optimization based on improved fish swarm algorithm is proposed in this paper. The improved algorithm is targeted on network coverage, node utilization rate and energy consumption balance, which makes use of the ergodic property of chaotic motion to overcome the disadvantage that arti...

This paper challenges the common assumption that swarm robotic systems are robust and scalable by default. We present an analysis based on both reliability modelling and experimental trials of a case study swarm performing team work, in which failures are deliberately induced. Our case study has been carefully chosen to represent a swarm task in which the overall desired system behaviour is an ...

Occasionally, medical decisions have to be taken in the absence of evidence-based guidelines. Other sources can be drawn upon to fill in the gaps, including experience and intuition. Authorities or experts, with their knowledge and experience, may provide further input--known as "eminence-based medicine". Due to the Internet and digital media, interactions among physicians now take place at a h...

Rapid advancements of both microsystem technology and multi-agent systems have generated a new discipline, arising from the fusion of microrobotics technologies and of swarm intelligence theories. Microrobotics contributes with new capabilities in manipulating objects in the microscale and in developing miniaturized intelligent machines, while swarm intelligence supplies new algorithms allowing...

A swarm-bot is a robotic entity built of several autonomous mobile robots (called s-bots) physically connected together. This form of collective robotics exploits robot interactions both at the behavioral and physical levels. The goal of this paper is to analyze the physical performance of a swarm-bot as function of its size (number n of s-bots composing it). We present three tasks and the corr...

The classification accuracy of the least squares support vector machine (LSSVM) models strongly depends on proper setting of its parameters. An optimal selection approach of LSSVM parameters is put forward based on multi-swarm cooperative chaos particle swarm optimization (MCCPSO) algorithm. Chaos particle swarm optimization (CPSO) can improve the ability of local search optimization with good ...

Tayebeh Mostajabi, Javad Poshtan Abstract— A central topic of swarm intelligence is the investigation of different types of emergent collective behaviors in swarms. This article focus on the swarm intelligence applications in control and system identification. Particle swarm optimization (PSO), a novel population based stochastic optimizer with fast convergence speed and simple implementation a...

In this chapter, Deep Memory with Particle Swarm Optimization (DMPSO) algorithm is presented, which is based on Particle Swarm Optimization initialized by the particles of Deep Memory Greedy Search (DMGS). The Particle Swarm Optimization (PSO) is a population based optimization technique, where the population is called a swarm. In PSO, each particle represents a possible solution to the optimiz...

1. Abstract Swarm algorithms such as Particle Swarm Optimization (PSO) are non-gradient probabilistic optimization algorithms that have been successfully applied to obtain global optimal solutions for complex problems such as multi-peak problems. However these algorithms have not been applied to complicated structural and mechanical optimization problems since local optimization capability is s...

We present Buzz, a novel programming language for heterogeneous robot swarms. Buzz advocates a compositional approach, offering primitives to define swarm behaviors both from the perspective of the single robot and of the overall swarm. Single-robot primitives include robot-specific instructions and manipulation of neighborhood data. Swarm-based primitives allow for the dynamic management of ro...