Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. In particular, the discipline focuses on the collective behaviors that result from the local interactions of the individuals with each other and with their environment. Examples of systems studied by swarm intelligenc...

Dimensionality reduction is a major task in remote sensing images. Feature selection is applied for performing dimensionality reduction. It selects the spectral features(i.e. Bands) and find a feature subset that preserves the semantics of the hyperspectral image. Based on particle swarm optimization (PSO), this paper proposes multi-objective functions for selecting the spectral feature subsets...

A number of different interaction modalities have been proposed for human engagement with networked systems. In this paper, we establish formal guarantees for whether or not a given such human-swarm interaction (HSI) strategy is appropriate for achieving particular multi-robot tasks, such as guiding a swarm of robots into a particular geometric configuration. In doing so, we define what it mean...

This paper presents a Swarm Intelligence based approach for sensor management of a multi sensor networks. Alternate sensor configurations and fusion strategies are evaluated by swarm agents, and an optimum configuration and fusion strategy evolves. An evolutionary algorithm, particle swarm optimization, is modified to optimize two objectives: accuracy and time. The output of the algorithm is th...

This paper addresses a vision based solution to collaborative multi-agent system for autonomous mobile robots. Each agent in the swarm is designed based on two different behavioural architectures, allowing them to overcome navigation problem in partly cluttered environment. A simple but efficient communication topology has been applied to the robot agents so as to run them in a swarm methodolog...

A control system design based on coupled nonlinear oscillators (CNOs) for a selforganized swarm system is presented. In this scheme, agents self-organize to flock and arrange group formations through attractive and repulsive forces among themselves using CNOs. Virtual agents are also used to create richer group formation patterns. The objective of the swarm control in this paper is to follow a ...

The job-shop scheduling problem has attracted many researchers’ attention in the past few decades, and many algorithms based on heuristic algorithms, genetic algorithms, and particle swarm optimization algorithms have been presented to solve it, respectively. Unfortunately, their results have not been satisfied at all yet. In this paper, a new hybrid swarm intelligence algorithm consists of par...

Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and selforganization. In particular, the discipline focuses on the collective behaviors that result from the local interactions of the individuals with each other and with their environment. Examples of systems studied by swarm intelligence...

Particle swarm optimization (PSO) is a novel swarm intelligent algorithm inspired by fish schooling and birds flocking. Due to the complex nature of engineering optimization tasks, the standard version can not always meet the optimization requirements. Therefore, in this paper, a new group decision mechanism is introduced to PSO to enhance the escaping capability from local optimum. Furthermore...