Swarm Intelligent Systems [electronic resource] / edited by Nadia Nedjah, Luiza de Macedo Mourelle.

By: Nedjah, Nadia [editor.]Contributor(s): Mourelle, Luiza de Macedo [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Studies in Computational Intelligence: 26Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006Description: XX, 184 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540338697Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
Methodologies Based on Particle Swarm Intelligence -- Swarm Intelligence: Foundations, Perspectives and Applications -- Waves of Swarm Particles (WoSP) -- Grammatical Swarm: A Variable-Length Particle Swarm Algorithm -- SWARMs of Self-Organizing Polymorphic Agents -- Experiences Using Particle Swarm Intelligence -- Swarm Intelligence — Searchers, Cleaners and Hunters -- Ant Colony Optimisation for Fast Modular Exponentiation using the Sliding Window Method -- Particle Swarm for Fuzzy Models Identification -- A Matlab Implementation of Swarm Intelligence based Methodology for Identification of Optimized Fuzzy Models.
In: Springer eBooksSummary: This volume offers a wide spectrum of sample works developed in leading research throughout the world about innovative methodologies of swarm intelligence and foundations of engineering swarm intelligent systems as well as applications and interesting experiences using the particle swarm optimisation. Swarm intelligence is an innovative computational way to solve hard problems which is at the heart of computational intelligence. In particular, particle swarm optimization, also commonly known as PSO, mimics the behavior of a swarm of insects or a school of fish. If one of the particle discovers a good path to food the rest of the swarm will be able to follow instantly even if they are far away in the swarm. Swarm behavior is modeled by particles in multidimensional space that have two characteristics: a position and a velocity. These particles wander around the hyperspace and remember the best position that they have discovered. They communicate good positions to each other and adjust their own position and velocity based on these good positions. Instead of designing complex and centralized systems, nowadays designers rather prefer to work with many small and autonomous agents. Each agent may prescribe to a global strategy. An agent acts on the simplest of rules. The many agents co-operating within the system can solve very complex problems with a minimal design effort. In General, multi-agent systems that use some swarm intelligence are said to be swarm intelligent systems. They are mostly used as search engines and optimization tools. The book should be useful both for beginners and experienced researchers in the field of computational intelligence.
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Methodologies Based on Particle Swarm Intelligence -- Swarm Intelligence: Foundations, Perspectives and Applications -- Waves of Swarm Particles (WoSP) -- Grammatical Swarm: A Variable-Length Particle Swarm Algorithm -- SWARMs of Self-Organizing Polymorphic Agents -- Experiences Using Particle Swarm Intelligence -- Swarm Intelligence — Searchers, Cleaners and Hunters -- Ant Colony Optimisation for Fast Modular Exponentiation using the Sliding Window Method -- Particle Swarm for Fuzzy Models Identification -- A Matlab Implementation of Swarm Intelligence based Methodology for Identification of Optimized Fuzzy Models.

This volume offers a wide spectrum of sample works developed in leading research throughout the world about innovative methodologies of swarm intelligence and foundations of engineering swarm intelligent systems as well as applications and interesting experiences using the particle swarm optimisation. Swarm intelligence is an innovative computational way to solve hard problems which is at the heart of computational intelligence. In particular, particle swarm optimization, also commonly known as PSO, mimics the behavior of a swarm of insects or a school of fish. If one of the particle discovers a good path to food the rest of the swarm will be able to follow instantly even if they are far away in the swarm. Swarm behavior is modeled by particles in multidimensional space that have two characteristics: a position and a velocity. These particles wander around the hyperspace and remember the best position that they have discovered. They communicate good positions to each other and adjust their own position and velocity based on these good positions. Instead of designing complex and centralized systems, nowadays designers rather prefer to work with many small and autonomous agents. Each agent may prescribe to a global strategy. An agent acts on the simplest of rules. The many agents co-operating within the system can solve very complex problems with a minimal design effort. In General, multi-agent systems that use some swarm intelligence are said to be swarm intelligent systems. They are mostly used as search engines and optimization tools. The book should be useful both for beginners and experienced researchers in the field of computational intelligence.

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