000 | 03170nam a22005415i 4500 | ||
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001 | 978-3-540-29938-7 | ||
003 | DE-He213 | ||
005 | 20160302161712.0 | ||
007 | cr nn 008mamaa | ||
008 | 100301s2005 gw | s |||| 0|eng d | ||
020 |
_a9783540299387 _9978-3-540-29938-7 |
||
024 | 7 |
_a10.1007/3-540-29938-6 _2doi |
|
050 | 4 | _aQA76.6-76.66 | |
072 | 7 |
_aUM _2bicssc |
|
072 | 7 |
_aCOM051000 _2bisacsh |
|
082 | 0 | 4 |
_a005.11 _223 |
100 | 1 |
_aTomassini, Marco. _eauthor. |
|
245 | 1 | 0 |
_aSpatially Structured Evolutionary Algorithms _h[electronic resource] : _bArtificial Evolution in Space and Time / _cby Marco Tomassini. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2005. |
|
300 |
_aXIII, 193 p. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aNatural Computing Series, _x1619-7127 |
|
505 | 0 | _aSetting the Stage for Structured Populations -- Island Models -- Island Models: Empirical Properties -- Lattice Cellular Models -- Lattice Cellular Models: Empirical Properties -- Random and Irregular Cellular Populations -- Coevolutionary Structured Models -- Some Nonconventional Models. | |
520 | _aEvolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and their empirical behavior are presented in detail. Moreover, there is new material on non-standard networked population structures such as small-world networks. The book should be of interest to advanced undergraduate and graduate students working in evolutionary computation, machine learning, and optimization. It should also be useful to researchers and professionals working in fields where the topological structures of populations and their evolution plays a role. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aComputer programming. | |
650 | 0 | _aComputers. | |
650 | 0 | _aAlgorithms. | |
650 | 0 | _aNumerical analysis. | |
650 | 0 | _aArtificial intelligence. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aProgramming Techniques. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aTheory of Computation. |
650 | 2 | 4 | _aComputation by Abstract Devices. |
650 | 2 | 4 | _aAlgorithm Analysis and Problem Complexity. |
650 | 2 | 4 | _aNumeric Computing. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783540241935 |
830 | 0 |
_aNatural Computing Series, _x1619-7127 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/3-540-29938-6 |
912 | _aZDB-2-SCS | ||
999 |
_c174145 _d174145 |