000 03984nam a22004935i 4500
001 978-3-540-33869-7
003 DE-He213
005 20161121231119.0
007 cr nn 008mamaa
008 100301s2006 gw | s |||| 0|eng d
020 _a9783540338697
_9978-3-540-33869-7
024 7 _a10.1007/978-3-540-33869-7
_2doi
050 4 _aTA329-348
050 4 _aTA640-643
072 7 _aTBJ
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
245 1 0 _aSwarm Intelligent Systems
_h[electronic resource] /
_cedited by Nadia Nedjah, Luiza de Macedo Mourelle.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2006.
300 _aXX, 184 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v26
505 0 _aMethodologies 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.
520 _aThis 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.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aNedjah, Nadia.
_eeditor.
700 1 _aMourelle, Luiza de Macedo.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540338680
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v26
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-33869-7
912 _aZDB-2-ENG
950 _aEngineering (Springer-11647)
999 _c508799
_d508799