Swarms within peer-to-peer networks are hindered by content containing incorrect metadata. After publishing, any incorrect metadata requires either a complete republish/swarm recreation or for each peer to manually make corrections (causing them to leave the swarm, decreasing performance). We present an approach which enables a swarm to both collaboratively upgrade embedded data to reflect chan...

Swarm Intelligence (SI) is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment causing coherent functional global patterns to emerge. The intelligence emerges from a chaotic balance between individuality and sociality. The chaotic balances are a characteristic feature of the complex system. Thi...

We describe a new class of decentralised control algorithms that link local wireless connectivity to low-level robot motion control in order to maintain both swarm aggregation and connectivity, whichwe term “coherence”, in unbounded space.We investigate the potential of first-order and second-order connectivity information to maintain swarm coherence. For the second-order algorithm we show that...

In this paper, we incorporate pheromone courtship mode of biology to improve particle swarm optimizer. The particle swarm optimization technique has ever since turned out to be a competitor in the field of numerical optimization. A particle swarm optimization consists of a number of individuals refining their knowledge of the given search space. Particle swarm optimizations are inspired by part...

In this paper, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two main phases of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Invasive weed optimization is the natureinspired algorithm which is inspired by colonial beha...

In order to improve performance of particle swarm optimization algorithm (PSO) in global optimization, the reason of premature convergence of the PSO is analyzed, and a new particle swarm optimization based on two subswarms (TSS-PSO) is proposed in this paper. The particle swarm is divided into two identical sub-swarms, that is, the first sub-swarm adopts basic PSO model to evolve, whereas the ...

When a colony of the swarm-founding social wasp Polybia occidentals loses its nest to severe weather or predation, the adult population evacuates and temporarily clusters on nearby foliage. Most of the adults remain inactive in the cluster, while foragers bring in nectar and scout wasps search the surrounding area for a new nesting site. After several hours, the scouts stimulate the rest of the...

Swarm based image analysis is a discipline, in which emphasis is on developing swarms with different rules and interactions for obtaining a specific emergent behavior, which may be used in an image analysis context. As the swarm process and results are readily visible, swarm based image analysis is an excellent discipline for obtaining a greater understanding of swarm theory. Currently there is...

This paper presents a novel and generic distributed swarm guidance algorithm using inhomogeneous Markov chains that guarantees superior performance over existing homogeneous Markov chain based algorithms, when the feedback of the current swarm distribution is available. The probabilistic swarm guidance using inhomogeneous Markov chain (PSG–IMC) algorithm guarantees sharper and faster convergenc...

Reactive power optimization is important to ensure power quality, improve system security, and reduce active power loss. So, this paper proposed parallel immune particle swarm optimization (PIPSO) algorithm. This algorithm makes basic particle swarm optimization (BPSO) and discrete particle swarm optimization (DPSO) to optimize in parallel, and improves the convergence capability of particle sw...