The emphasis in swarm intelligence research is on the division of tasks needed to keep the swarm functioning. The topic of this paper is on macroscopical patterns emerging from interacting swarm members and the environment. It is argued that these patterns are invaluable for maintaining the integrity of the swarm. A preliminary catalogue of macroscopical patterns and an experimental method are ...

The basic thought of particle swarm optimization is introduced firstly, then particle swarm optimization algorithm model is established. The application of the improved particle swarm optimization algorithm to power supply system fault diagnosis is analyzed in accordance with problem of the algorithm, and migration strategy is added to particle swarm optimization algorithm. Finally the paramete...

When grown in a rich medium on agar, many bacteria elongate, produce more flagella, and swim in a thin film of fluid over the agar surface in swirling packs. Cells that spread in this way are said to swarm. The agar is a solid gel, with pores smaller than the bacteria, so the swarm/agar interface is fixed. Here we show, in experiments with Escherichia coli, that the swarm/air interface also is ...

This paper presents a new multi-objective optimization algorithm in which multi-swarm cooperative strategy is incorporated into particle swarm optimization algorithm, called multi-swarm cooperative multi-objective particle swarm optimizer (MC-MOPSO). This algorithm consists of multiple slave swarms and one master swarm. Each slave swarm is designed to optimize one objective function of the mult...

A swarm is a ‘‘complex adaptive system’’, which is decentralized and self-organized and whose individuals are simple, homogeneous and autonomous. Swarm intelligence is defined to describe its emergent behaviors. Both wireless sensor networks and mobile multi-robots demonstrate swarm features. This paper first discusses the challenges of combining wireless sensor networks and mobile multi-robots...

Midges (Anarete pritchardi) coordinate their flight motions to form a cohesive group during swarming. In this paper, individual midge motion dynamics, sensing abilities, and flight rules are represented with a midge swarm model. The sensing accuracy and flight rule are adjusted so that the model produces trajectory behavior, and velocity, speed, and acceleration distributions, that are remarkab...

by MICHAEL ANTHONY KOVACINA This work implements and demonstrates a set of tools to automatically generate swarm algorithms. SWEEP, SWarm Experimentation and Evaluation Platform, a swarm algorithm development and simulation platform is implemented. To demonstrate the utility of SWEEP, several swarm-based algorithms are constructed for free-moving and dynamics-constrained agents, culminating in ...

In this paper, we propose three specific scenarios in order to allow one to analyze the performance of swarmintelligence based coordination models for swarm of robots. The specific scenarios aim to assess some features presented on swarm robots: (i) contraction and expansion; (ii) selfsegregation and self-aggregation; and (iii) the capacity to change abruptly the fly direction whenever it is ne...

Standard particle swarm optimization is easy to fall into local optimum and has the problem of low precision. To solve these problems, the paper proposes an effective approach, called particle swarm optimization based on multiple swarms and opposition-based learning, which divides swarm into two subswarms. The 1st sub-swarm employs PSO evolution model in order to hold the self-learning ability;...

Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. 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 are colonies ...