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140501s2004 si ob 001 0 eng d |
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|a QA76.9.D5 ǂb S82 2004eb
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|a 004
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|a UAMI
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|a Subbu, Raj.
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|a Network-Based Distributed Planning Using Coevolutionary Algorithms.
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260 |
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|a Singapore :
|b World Scientific Publishing Company,
|c 2004.
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300 |
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|a 1 online resource (193 pages)
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336 |
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|a text
|b txt
|2 rdacontent
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337 |
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|a computer
|b c
|2 rdamedia
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338 |
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|a online resource
|b cr
|2 rdacarrier
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490 |
1 |
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|a Series in Intelligent Control and Intelligent Automation
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0 |
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|a Print version record.
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520 |
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|a In this book, efficient and scalable coevolutionary algorithms for distributed, network-based decision-making, which utilize objective functions are developed in a networked environment where internode communications are a primary factor in system performance. A theoretical foundation for this class of coevolutionary algorithms is introduced using techniques from stochastic process theory and mathematical analysis. A case study in distributed, network-based decision-making presents an implementation and detailed evaluation of the coevolutionary decision-making framework that incorporates distr.
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504 |
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|a Includes bibliographical references (pages 159-168) and index.
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505 |
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|a 1. Introduction. 1.1. Motivation. 1.2. Approach. 1.3. Principal contributions. 1.4. Book outline -- 2. Background and related work. 2.1. Collaborative manufacturing. 2.2. Combinatorial optimization. 2.3. Evolutionary algorithms. 2.4. Agents. 2.5. Distributed problem solving -- 3. Problem formulation and analysis. 3.1. Introduction. 3.2. General problem formulation. 3.3. Printed circuit assembly problem. 3.4. Algorithm applicability analysis -- 4. Theory and analysis of evolutionary optimization. 4.1. Introduction. 4.2. Theoretical foundation. 4.3. Convergence analysis -- 5. Theory and analysis of distributed coevolutionary optimization. 5.1. Introduction. 5.2. Theory. 5.3. Computational delay analysis -- 6. Performance evaluation based on ideal objectives. 6.1. Introduction. 6.2. Gaussian objectives. 6.3. Planar tile layout problems. 6.4. Design-supplier-manufacturing problem -- 7. Coevolutionary virtual design environment. 7.1. Introduction. 7.2. Application domain. 7.3. Evolutionary optimization. 7.4. Simulation environments -- 8. Evaluation and analysis. 8.1. Introduction. 8.2. Nature and evolution of planning decisions. 8.3. Strategy for performance evaluation. 8.4. Performance evaluation. 8.5. Applicability analysis of the frameworks -- 9. Conclusions. 9.1. Summary. 9.2. Future work.
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590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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650 |
|
0 |
|a Electronic data processing
|x Distributed processing.
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650 |
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0 |
|a Algorithms.
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650 |
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0 |
|a Intelligent agents (Computer software)
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650 |
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2 |
|a Algorithms
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650 |
|
6 |
|a Traitement réparti.
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650 |
|
6 |
|a Algorithmes.
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650 |
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6 |
|a Agents intelligents (Logiciels)
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650 |
|
7 |
|a algorithms.
|2 aat
|
650 |
|
7 |
|a Algorithms
|2 fast
|
650 |
|
7 |
|a Electronic data processing
|x Distributed processing
|2 fast
|
650 |
|
7 |
|a Intelligent agents (Computer software)
|2 fast
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700 |
1 |
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|a Sanderson, A. C.
|q (Arthur C.)
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776 |
0 |
8 |
|i Print version:
|z 9789812387547
|
830 |
|
0 |
|a Series in intelligent control and intelligent automation.
|
856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1679472
|z Texto completo
|
938 |
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|a EBL - Ebook Library
|b EBLB
|n EBL1679472
|
994 |
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|a 92
|b IZTAP
|