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Готові списки джерел за темами / Combinatorial nature / Книги

Книги з теми "Combinatorial nature"

Щоб переглянути інші типи публікацій з цієї теми, перейдіть за посиланням: Combinatorial nature.

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 29 січня 2023

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1

Coello, Carlos A. Coello. Advances in multi-objective nature inspired computing. Berlin: Springer, 2010.

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2

Rudin, Donald O. The Nature of the world: New horizons for mankind. Annapolis, Md: Core Books, 1998.

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3

Rothlauf, Franz. Design of modern heuristics: Principles and application. Heidelberg: Springer, 2011.

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4

P, Devlin John, ed. High throughput screening: The discovery of bioactive substances. New York: M. Dekker, 1997.

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5

Model theoretic methods in finite combinatorics: AMS-ASL special session, January 5-8, 2009 Washington, DC. Providence, R.I: American Mathematical Society, 2011.

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6

Chiong, Raymond, and Sandeep Dhakal. Natural intelligence for scheduling, planning and packing problems. Berlin: Springer, 2009.

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7

1948-, Bartlett Paul Allan, and Entzeroth Michael, eds. Exploiting chemical diversity for drug discovery. Cambridge: RSC Publishing, 2006.

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8

Reverse chemical genetics: Methods and protocols. New York, NY: Humana Press, 2009.

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9

Chemogenomics: Methods and applications. New York, NY: Humana Press, 2009.

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10

Cozzens, Margaret B. Biomath in the schools. Providence, R.I: American Mathematical Society, 2011.

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11

Litvinov, G. L. (Grigoriĭ Lazarevich), 1944- editor of compilation and Sergeev, S. N., 1981- editor of compilation, eds. Tropical and idempotent mathematics and applications: International Workshop on Tropical and Idempotent Mathematics, August 26-31, 2012, Independent University, Moscow, Russia. Providence, Rhode Island: American Mathematical Society, 2014.

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12

Coello, Carlos Coello, Clarisse Dhaenens, and Laetitia Jourdan. Advances in Multi-Objective Nature Inspired Computing. Springer, 2012.

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13

Coello, Carlos A. Coello, Clarisse Dhaenens, and Laetitia Jourdan. Advances in Multi-Objective Nature Inspired Computing. Springer, 2010.

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14

Tanasa, Adrian. Combinatorial Physics. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192895493.001.0001.

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Анотація:

After briefly presenting (for the physicist) some notions frequently used in combinatorics (such as graphs or combinatorial maps) and after briefly presenting (for the combinatorialist) the main concepts of quantum field theory (QFT), the book shows how algebraic combinatorics can be used to deal with perturbative renormalisation (both in commutative and non-commutative quantum field theory), how analytic combinatorics can be used for QFT issues (again, for both commutative and non-commutative QFT), how Grassmann integrals (frequently used in QFT) can be used to proCve new combinatorial identities (generalizing the Lindström–Gessel–Viennot formula), how combinatorial QFT can bring a new insight on the celebrated Jacobian conjecture (which concerns global invertibility of polynomial systems) and so on. In the second part of the book, matrix models, and tensor models are presented to the reader as QFT models. Several tensor model results (such as the implementation of the large N limit and of the double-scaling limit for various such tensor models, N being here the size of the tensor) are then exposed. These results are natural generalizations of results extensively used by theoretical physicists in the study of matrix models and they are obtained through intensive use of combinatorial techniques (this time mainly enumerative techniques). The last part of the book is dedicated to the recently discovered relation between tensor models and the holographic Sachdev–Ye–Kitaev model, model which has been extensively studied in the last years by condensed matter and by high-energy physicists.

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15

Combinatorial Synthesis of Natural Product-Based Libraries (Critical Reviews in Combinatorial Chemistry). CRC, 2006.

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16

Boldi, Armen M. Combinatorial Synthesis of Natural Product-Based Libraries. Taylor & Francis Group, 2006.

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17

Boldi, Armen M. Combinatorial Synthesis of Natural Product-Based Libraries. Taylor & Francis Group, 2019.

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18

Boldi, Armen M. Combinatorial Synthesis of Natural Product-Based Libraries. Taylor & Francis Group, 2006.

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19

Boldi, Armen M. Combinatorial Synthesis of Natural Product-Based Libraries. Taylor & Francis Group, 2006.

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20

Boldi, Armen M. Combinatorial Synthesis of Natural Product-Based Libraries. Taylor & Francis Group, 2006.

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21

Pierrepont, Alexandre. The Salmon of Wisdom. Edited by George E. Lewis and Benjamin Piekut. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780195370935.013.28.

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Анотація:

This chapter scrutinizes the universe of representations of creative musicians, especially in the combinatorial and transformative dynamics of the jazzistic field. The poetics of improvisation encompasses both analytical analogical thought, through a dialogic treatment of oppositions rendered complementary, while allowing the discovery and practice of one’s own plurality: one’s self and self’s other. For improvisers, a continuum of multiple meanings may be played out in and around oneself, without abdicating clarity of conscience or the acuity of contexts and structures. In the act of improvisation, placing oneself in streams of unconsciousness and hyperconsciousness, as well as double and multiple consciousness, poses critical questions around the changing nature of identities and alterities.

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22

Darrigol, Olivier. The Probabilistic Turn (1876–1884). Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198816171.003.0005.

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This chapter deals with writings in which Boltzmann expressed the statistical nature of the entropy law and temporarily made the relation between entropy and combinatorial probability a basic constructive tool of his theory. In 1881, he discovered that this relation derived from what we now call the microcanonical distribution, and he approved Maxwell’s recent foundation of the equilibrium problem on the microcanonical ensemble. Boltzmann also kept working on problems he had tackled in earlier years. He proposed a new solution to the problem of specific heats, and he performed enormous calculations for the viscosity and diffusion coefficients in the hard-ball model. In a lighter genre, he conceived a new way of determining molecular sizes, and he speculated on a gas model in which the molecular forces would be entirely attractive.

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23

Russell, Jeffrey Sanford, and John Hawthorne. Possible Patterns. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198828198.003.0005.

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Анотація:

“There are no gaps in logical space,” writes Lewis (1986), giving voice to sentiment shared by many philosophers. But different natural ways of trying to make this sentiment precise turn out to conflict with one another. One is a pattern idea: “Any pattern of instantiation is metaphysically possible.” Another is a cut and paste idea: “For any objects in any worlds, there exists a world that contains any number of duplicates of all of those objects.” Jumping off from discussions from Forrest and Armstrong (1984) and Nolan (1996), the authors use resources from model theory to show the inconsistency of certain packages of combinatorial principles and the consistency of others.

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24

Guionnet, Alice. Free probability. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198797319.003.0003.

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Анотація:

Free probability was introduced by D. Voiculescu as a theory of noncommutative random variables (similar to integration theory) equipped with a notion of freeness very similar to independence. In fact, it is possible in this framework to define the natural ‘free’ counterpart of the central limit theorem, Gaussian distribution, Brownian motion, stochastic differential calculus, entropy, etc. It also appears as the natural setup for studying large random matrices as their size goes to infinity and hence is central in the study of random matrices as their size go to infinity. In this chapter the free probability framework is introduced, and it is shown how it naturally shows up in the random matrices asymptotics via the so-called ‘asymptotic freeness’. The connection with combinatorics and the enumeration of planar maps, including loop models, are discussed.

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25

Downey, Rod, and Noam Greenberg. A Hierarchy of Turing Degrees. Princeton University Press, 2020. http://dx.doi.org/10.23943/princeton/9780691199665.001.0001.

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Анотація:

Computability theory is a branch of mathematical logic and computer science that has become increasingly relevant in recent years. The field has developed growing connections in diverse areas of mathematics, with applications in topology, group theory, and other subfields. This book introduces a new hierarchy that allows them to classify the combinatorics of constructions from many areas of computability theory, including algorithmic randomness, Turing degrees, effectively closed sets, and effective structure theory. This unifying hierarchy gives rise to new natural definability results for Turing degree classes, demonstrating how dynamic constructions become reflected in definability. The book presents numerous construction techniques involving high-level nonuniform arguments, and their self-contained work is appropriate for graduate students and researchers. Blending traditional and modern research results in computability theory, the book establishes novel directions in the field.

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26

Mancosu, Paolo, Sergio Galvan, and Richard Zach. An Introduction to Proof Theory. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192895936.001.0001.

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Анотація:

Proof theory is a central area of mathematical logic of special interest to philosophy. It has its roots in the foundational debate of the 1920s, in particular, in Hilbert’s program in the philosophy of mathematics, which called for a formalization of mathematics, as well as for a proof, using philosophically unproblematic, “finitary” means, that these systems are free from contradiction. Structural proof theory investigates the structure and properties of proofs in different formal deductive systems, including axiomatic derivations, natural deduction, and the sequent calculus. Central results in structural proof theory are the normalization theorem for natural deduction, proved here for both intuitionistic and classical logic, and the cut-elimination theorem for the sequent calculus. In formal systems of number theory formulated in the sequent calculus, the induction rule plays a central role. It can be eliminated from proofs of sequents of a certain elementary form: every proof of an atomic sequent can be transformed into a “simple” proof. This is Hilbert’s central idea for giving finitary consistency proofs. The proof requires a measure of proof complexity called an ordinal notation. The branch of proof theory dealing with mathematical systems such as arithmetic thus has come to be called ordinal proof theory. The theory of ordinal notations is developed here in purely combinatorial terms, and the consistency proof for arithmetic presented in detail.

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27

Springer, Sandeep Dhakal, and Raymond Chiong. Natural Intelligence for Scheduling, Planning and Packing Problems. Springer Berlin / Heidelberg, 2012.

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28

Mulzer, J. The Role of Natural Products in Drug Discovery. Edited by J. Mulzer. Springer, 2001.

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29

Koga, Hisashi. Reverse Chemical Genetics: Methods and Protocols. Humana Press, 2012.

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30

Jacoby, Edgar. Chemogenomics: Methods and Applications. Humana Press, 2012.

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