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Libros sobre el tema "Algorithems"

Autor: Grafiati
Publicado: 6 de septiembre de 2023
Última modificación: 31 de julio de 2025

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1

Smith, Jeffrey Dean. Design and analysis of algorithms. PWS-KENT Pub. Co., 1989.

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2

Berlinski, David. The advent of the algorithm: The idea that rules the world. Harcourt, 2000.

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3

Baase, Sara. Computer algorithms: Introduction to design and analysis. 2nd ed. Addison-Wesley Pub. Co., 1991.

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4

Baase, Sara. Computer algorithms: Introduction to design and analysis. 2nd ed. Addison-Wesley Pub. Co., 1988.

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5

Müller-Hannemann, Matthias, and Stefan Schirra. Algorithm engineering: Bridging the gap between algorithm theory and practice. Springer, 2010.

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6

H, Jamieson Leah, Gannon Dennis B. 1947-, and Douglass Robert J, eds. The characteristics of parallel algorithms. MIT Press, 1987.

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7

Lance, Chambers, ed. The practical handbook of genetic algorithms: Applications. 2nd ed. Chapman & Hall/CRC, 2001.

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8

Paul, Bratley, ed. Fundamentals of algorithmics. Prentice Hall, 1996.

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9

Feldbauer, Martin. Martin Feldbauer: Allmächtiger Algorithmus = Almighty algorithm. Syker Vorwerk, 2017.

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10

Brent, R. P. Algorithms for minimization without derivatives. Dover Publications, 2002.

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11

Chang, Lin, William D. Chey, John Kellow, Jan Tack, and William E. Whitehead, eds. Rome IV Diagnostic Algorithms. The Rome Foundation, 2016. http://dx.doi.org/10.24890/algorithms.

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12

Dr, Herrera Francisco, and Verdegay José-Luis, eds. Genetic algorithms and soft computing. Physica-Verlag, 1996.

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13

Evripidis, Bampis, Jansen Klaus, and Kenyon Claire, eds. Efficient approximation and online algorithms: Recent progress on classical combinatorical optimization problems and new applications. Springer, 2006.

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14

Evripidis, Bampis, Jansen Klaus, and Kenyon Claire, eds. Efficient approximation and online algorithms: Recent progress on classical combinatorical optimization problems and new applications. Springer, 2006.

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15

K, Agarwal Pankaj, Kavraki Lydia, and Mason Matthew T, eds. Robotics: The algorithmic perspective : the Third Workshop on the Algorithmic Foundations of Robotics. A K Peters, 1998.

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16

-P, Laumond J., and Overmars Mark H. 1958-, eds. Algorithms for robotic motion and manipulation: 1996 Workshop on the Algorithmic Foundations of Robotics. A K Peters, 1997.

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17

R, Donald Bruce, Lynch Kevin, and Rus Daniela, eds. Algorithmic and computational robotics: New directions : the fourth Workshop on the Algorithmic Foundations of Robotics. AK Peters, 2001.

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18

Hutchinson, Alan. Algorithmic learning. Clarendon Press, 1994.

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19

Workshop, WADS '89 (1989 Ottawa Ont ). Algorithms and data structures: Workshop WADS '89, Ottawa, Canada, August 17-19, 1989 : proceedings. Springer-Verlag, 1989.

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20

Wilf, Herbert S. Algorithms and complexity. Prentice-Hall, 1986.

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21

Alan, Gibbons. Efficient parallel algorithms. Cambridge University Press, 1988.

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22

Weimin, Wu, Cardullo Frank M, and Langley Research Center, eds. Motion cueing algorithm development: Initial investigation and redesign of the algorithms. National Aeronautics and Space Administration, Langley Research Center, 2000.

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23

Lance, Chambers, ed. Practical handbook of genetic algorithms. CRC Press, 1995.

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24

Jacques, Calmet, and Laboratoire d'informatique fondamentale et d'intelligence artificielle (Saint-Martin d'Hères, France), eds. Algebraic algorithms and error-correcting codes: 3rd international conference, AAECC-3, Grenoble, France, July 15-19, 1985, proceedings. Springer-Verlag, 1986.

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25

(Editor), Lawrence D. Davis, Kenneth De Jong (Editor), Michael D. Vose (Editor), and L. Darrell Whitley (Editor), eds. Evolutionary Algorithms (The IMA Volumes in Mathematics and its Applications). Springer, 1999.

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26

Berlinski, David. The Advent of the Algorithm: The 300-Year Journey from an Idea to the Computer. Harvest Books, 2001.

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27

Baase, Sara. Computer Algorithms: An Introduction to Design & Analysis. Addison-Wesley, 2001.

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28

James, Evans. Optimization Algorithms for Networks and Graphs. Taylor & Francis Group, 2017.

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29

James, Evans. Optimization Algorithms for Networks and Graphs. Taylor & Francis Group, 2017.

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30

Müller-Hannemann, Matthias, and Stefan Schirra. Algorithm Engineering: Bridging the Gap Between Algorithm Theory and Practice. Springer London, Limited, 2010.

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31

Optimization Algorithms for Networks and Graphs. Taylor & Francis Group, 2017.

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32

Diagrams, types, algorithms: Diagramme, Typen, Algorithmen. Editions Selene, 2001.

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33

Algorithm engineering for integral and dynamic problems. Gordon & Breach, 2001.

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34

Chambers, Lance. Practical Handbook of Genetic Algorithms: Applications. Taylor & Francis Group, 2001.

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35

Chambers, Lance. Practical Handbook of Genetic Algorithms. Taylor & Francis Group, 2020.

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36

Bleakley, Chris. Poems That Solve Puzzles. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198853732.001.0001.

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Algorithms are the hidden methods that computers apply to process information and make decisions. The book tells the story of algorithms from their ancient origins to the present day and beyond. The book introduces readers to the inventors and events behind the genesis of the world’s most important algorithms. Along the way, it explains, with the aid of examples and illustrations, how the most influential algorithms work. The first algorithms were invented in Mesopotamia 4,000 years ago. The ancient Greeks refined the concept, creating algorithms for finding prime numbers and enumerating Pi. A
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37

Sedgewick, Robert. Algorithms (Addison-Wesley series in computer science). Addison Wesley Longman Publishing Co, 1998.

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38

Bucher, Taina. The Multiplicity of Algorithms. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190493028.003.0002.

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Algorithms exist and operate on multiple levels. They are technical as much as they are social, cultural as much as they are functional. The chapter examines the multiplicity of algorithms, arguing for an expanded view on algorithms that takes it variable ontology into account. Providing the conceptual groundwork by merging perspectives from computer science, social sciences, and the humanities, the chapter explains the different meanings of algorithms as technical entities, and phenomena of social concern, respectively. Algorithms do not merely have power and politics; they are fundamentally
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39

Design Analysis and Algorithms: Analysis of algorithm, Advanced Data Structure, Algorithm Analysis. University Science Press, 2008.

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40

Algorithms and Subjectivity. Taylor & Francis Group, 2021.

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41

Algorithms and Subjectivity: The Subversion of Critical Knowledge. Taylor & Francis Group, 2024.

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42

Algorithms. MIT Press, 2020.

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43

(Editor), Bruce R. Donald, Kevin M. Lynch (Editor), and Daniela Rus (Editor), eds. Algorithmic and Computational Robotics: New Directions. AK Peters, Ltd., 2001.

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44

Dortmund, Universität, ed. Genetic algorithms and population structures: A massively parallel algorithm. 1991.

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45

Petreschi, Rossella, and Giorgio Ausiello. Power of Algorithms: Inspiration and Examples in Everyday Life. Springer London, Limited, 2013.

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46

Algorithmic Cryptanalysis (Chapman & Hall/Crc Cryptography and Network Security). Chapman & Hall/CRC, 2009.

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47

Gibbons, Alan, and Wojciech Rytter. Efficient Parallel Algorithms. Cambridge University Press, 1989.

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48

Godwin Premi, Dr M. S., Dr D. Susitra, Dr Suja Cherukullapurath Mana, Ms R. Velvizhi, and Ms Manju C. Nair. QUANTUM COMPUTING. Magestic Technology Solutions (P) Ltd, Chennai, Tamil Nadu, India, 2025. https://doi.org/10.47716/978-93-92090-62-2.

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Quantum Computing represents a paradigm shift in computation, leveraging the principles of quantum mechanics to solve problems intractable for classical computers. This book provides a comprehensive exploration of quantum computing, encompassing its foundational concepts, architecture, algorithms, programming techniques, and real-world applications. Beginning with an overview and historical evolution, it delves into the fundamental differences between classical and quantum computing, highlighting key quantum mechanical phenomena such as superposition, entanglement, and interference. The book f
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49

Machine Learning: Algorithms and Applications. Taylor & Francis Group, 2016.

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50

Chambers, Lance D. Practical Handbook of Genetic Algorithms: Applications, Second Edition. Taylor & Francis Group, 2000.

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