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...

Swarm intelligence is the collective problem-solving behavior of groups of animals and artificial agents. Often, swarm intelligence is the result of self-organization, which emerges from the agents’ local interactions with one another and with their environment. Such local interactions can be positive, negative, or neutral. Positive interactions help a swarm of agents solve a problem. Negative ...

In this paper we propose a new method to improve the performance of hierarchical classification. We use a swarm intelligence algorithm to select the type of classification algorithm to be used at each “classifier node” in a classifier tree. These classifier nodes are used in a top-down divide and conquer fashion to classify the examples from hierarchical data sets. In this paper we propose a sw...

Image compression is one of the most important and successful applications of the wavelet transform. Images will have huge amount of information which require more storage space, and high transmission bandwidths and more transmission time. So it is important to compress the image by eliminating the redundant information in the image and encoding only the essential information. As multimedia inf...

Firefly algorithm is a recently added member of the swarm intelligence heuristics family. In this paper the firefly algorithm is adjusted and applied to integer programming problems. In order to deal with integer programming problems, firefly algorithm rounds the parameter values to the closest integer after producing new solutions. The performance of firefly algorithm is tested on seven proble...

For a decade swarm Intelligence, an artificial intelligence discipline, is concerned with the design of intelligent multi-agent systems by taking inspiration from the collective behaviors of social insects and other animal societies. They are characterized by a decentralized way of working that mimics the behavior of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with ...

This chapter introduces a swarm intelligence-inspired approach for target allocation in large teams of autonomous robots. For this purpose, the Distributed Bees Algorithm (DBA) was proposed and developed by the authors. The algorithm allows decentralized decision-making by the robots based on the locally available information, which is an inherent feature of animal swarms in nature. The algorit...

Swarm intelligence was originally inspired in social behaviour in nature, also considering the evolving aspects, several variations in swarm intelligence’s techniques made it applicable to optimization problems. In this paper two case studies of static environment, composed with obstacles are presented and evaluated, a comparative study is evaluated between two techniques of swarm intelligence ...

The process of load balancing increases the performance of cloud based services. Cloud based service provide hardware, software and platform as service. For the balancing of public cloud used two types of approach one is traditional approach and other is dynamic approach. The traditional approach follows the concept of CPU scheduling technique such as round robin and first come first service. T...

In the context of spectrum surveillance, a new method to recover the code of spread spectrum signal is presented, while the receiver has no knowledge of the transmitter’s spreading sequence. In our previous paper, we used Genetic algorithm (GA), to recover spreading code. Although genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems, but nonethel...