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 ...

This paper systematically presents the Swarm Intelligence (SI) methods for optimization of multiple and many objective problems. The fundamental difference of Multiple andMany Objective Optimization problems have been studied very rigorously. The three forefront swarm intelligence methods, i.e., Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony Optimiza...

This paper presents a novel swarm intelligence inspired routing algorithm (EARA) for mobile ad hoc networks. Based on the understanding of the evolutionary cooperation in the biological swarm, which provides an alternative solution resilient against changes in the dynamic environment, We use the principle of swarm intelligence for the reinforcement of optimal routes with only local communicatio...

0968-090X/$ see front matter 2008 Published b doi:10.1016/j.trc.2008.03.002 E-mail address: [email protected] Agent-based modeling is an approach based on the idea that a system is composed of decentralized individual ‘‘agents” and that each agent interacts with other agents according to localized knowledge. Special kinds of artificial agents are the agents created by analogy with social inse...

Swarm robots are special multi-robots and usually considered being controlled with swarm intelligence-basedmethod to complete some assigned complex tasks (Dorigo and Sahin, 2004). Similar to the biological counterparts in nature, swarm intelligence among such artificial system is emerged from local interactions between individual robots or individual robot and its environment (Beni, 2005; Şahin...

In this paper, the authors focus on swarm intelligence represented by the ant colony system and artificial neural network simulating the brain working principles, and analyse the similarities between them by the approaches of a complexity study. Firstly, the similarities between swarm intelligence and neural network have been analysed qualitatively from system structure and operation mechanisms...

Swarm intelligence algorithms are inherently parallel since different individuals in the swarm perform independent computations at different positions simultaneously. Hence, these algorithms lend themselves well to parallel implementations thereby speeding up the optimization process. FireWorks Algorithm (FWA) is a recently proposed swarm intelligence algorithm for optimization. This work inves...

The SWarm Intelligence-based Reinforcement Learning (SWIRL) method is proposed in this paper to efficiently generate Artificial Neural Network (ANN) based solutions to various problems. Basically, two swarm intelligence based algorithms are combined together in SWIRL to train the ANN models. Ant Colony Optimization (ACO) is applied to optimize ANN topology, while Particle Swarm Optimization (PS...