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008 | 150903s2013 gw | o |||| 0|eng d | ||
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_a9783642340970 _99783642340970 |
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024 | 7 |
_a10.1007/9783642340970 _2doi |
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_a201509031011 _bVLOAD _c201405070259 _dVLOAD _y201402201431 _zstaff |
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_aMX-SnUAN _bspa _cMX-SnUAN _erda |
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050 | 4 | _aQ342 | |
100 | 1 |
_aCzarnowski, Ireneusz. _eeditor. _9345764 |
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245 | 1 | 0 |
_aAgent-Based Optimization / _cedited by Ireneusz Czarnowski, Piotr J?drzejowicz, Janusz Kacprzyk. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013. |
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300 |
_ax, 203 páginas 38 ilustraciones _brecurso en línea. |
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336 |
_atexto _btxt _2rdacontent |
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337 |
_acomputadora _bc _2rdamedia |
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_arecurso en línea _bcr _2rdacarrier |
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_aarchivo de texto _bPDF _2rda |
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490 | 0 |
_aStudies in Computational Intelligence, _x1860-949X ; _v456 |
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500 | _aSpringer eBooks | ||
505 | 0 | _aMachine Learning and Multiagent Systems as Interrelated Technologies -- Ant Colony Optimization for the Multi-criteria Vehicle Navigation Problem -- Solving Instances of the Capacitated Vehicle Routing Problem Using Multi-Agent Non-Distributed and Distributed Environment -- Structure vs. Efficiency of the Cross-Entropy Based Population Learning Algorithm for Discrete-Continuous Scheduling with Continuous Resource Discretisation -- Triple-Action Agents Solving the MRCPSP/max Problem -- Team of A-Teams - a Study of the Cooperation Between Program Agents Solving Difficult Optimization Problems -- Distributed Bregman-Distance Algorithms for Min-Max Optimization -- A Probability Collectives Approach for Multi-Agent Distributed and Cooperative Optimization with Tolerance for Agent Failure. | |
520 | _aThis volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving. | ||
590 | _aPara consulta fuera de la UANL se requiere clave de acceso remoto. | ||
700 | 1 |
_aJ?drzejowicz, Piotr. _eeditor. _9339469 |
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700 | 1 |
_aKacprzyk, Janusz. _eeditor. _9323670 |
|
710 | 2 |
_aSpringerLink (Servicio en línea) _9299170 |
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776 | 0 | 8 |
_iEdición impresa: _z9783642340963 |
856 | 4 | 0 |
_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-642-34097-0 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL) |
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