computational complexity a modern approach

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Computational Complexity

Author : Sanjeev Arora
ISBN : 1139477366
Genre : Computers
File Size : 85. 49 MB
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This beginning graduate textbook describes both recent achievements and classical results of computational complexity theory. Requiring essentially no background apart from mathematical maturity, the book can be used as a reference for self-study for anyone interested in complexity, including physicists, mathematicians, and other scientists, as well as a textbook for a variety of courses and seminars. More than 300 exercises are included with a selected hint set. The book starts with a broad introduction to the field and progresses to advanced results. Contents include: definition of Turing machines and basic time and space complexity classes, probabilistic algorithms, interactive proofs, cryptography, quantum computation, lower bounds for concrete computational models (decision trees, communication complexity, constant depth, algebraic and monotone circuits, proof complexity), average-case complexity and hardness amplification, derandomization and pseudorandom constructions, and the PCP theorem.

Computational Complexity

Author :
ISBN : 7510042860
Genre : Computational complexity
File Size : 67. 96 MB
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Concise Guide To Computation Theory

Author : Akira Maruoka
ISBN : 0857295357
Genre : Computers
File Size : 56. 60 MB
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This textbook presents a thorough foundation to the theory of computation. Combining intuitive descriptions and illustrations with rigorous arguments and detailed proofs for key topics, the logically structured discussion guides the reader through the core concepts of automata and languages, computability, and complexity of computation. Topics and features: presents a detailed introduction to the theory of computation, complete with concise explanations of the mathematical prerequisites; provides end-of-chapter problems with solutions, in addition to chapter-opening summaries and numerous examples and definitions throughout the text; draws upon the author’s extensive teaching experience and broad research interests; discusses finite automata, context-free languages, and pushdown automata; examines the concept, universality and limitations of the Turing machine; investigates computational complexity based on Turing machines and Boolean circuits, as well as the notion of NP-completeness.

Computational Complexity

Author : Oded Goldreich
ISBN : 9781139472746
Genre : Computers
File Size : 75. 33 MB
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Complexity theory is a central field of the theoretical foundations of computer science. It is concerned with the general study of the intrinsic complexity of computational tasks; that is, it addresses the question of what can be achieved within limited time (and/or with other limited natural computational resources). This book offers a conceptual perspective on complexity theory. It is intended to serve as an introduction for advanced undergraduate and graduate students, either as a textbook or for self-study. The book will also be useful to experts, since it provides expositions of the various sub-areas of complexity theory such as hardness amplification, pseudorandomness and probabilistic proof systems. In each case, the author starts by posing the intuitive questions that are addressed by the sub-area and then discusses the choices made in the actual formulation of these questions, the approaches that lead to the answers, and the ideas that are embedded in these answers.

Logical Foundations Of Mathematics And Computational Complexity

Author : Pavel Pudlák
ISBN : 9783319001197
Genre : Mathematics
File Size : 88. 80 MB
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The two main themes of this book, logic and complexity, are both essential for understanding the main problems about the foundations of mathematics. Logical Foundations of Mathematics and Computational Complexity covers a broad spectrum of results in logic and set theory that are relevant to the foundations, as well as the results in computational complexity and the interdisciplinary area of proof complexity. The author presents his ideas on how these areas are connected, what are the most fundamental problems and how they should be approached. In particular, he argues that complexity is as important for foundations as are the more traditional concepts of computability and provability. Emphasis is on explaining the essence of concepts and the ideas of proofs, rather than presenting precise formal statements and full proofs. Each section starts with concepts and results easily explained, and gradually proceeds to more difficult ones. The notes after each section present some formal definitions, theorems and proofs. Logical Foundations of Mathematics and Computational Complexity is aimed at graduate students of all fields of mathematics who are interested in logic, complexity and foundations. It will also be of interest for both physicists and philosophers who are curious to learn the basics of logic and complexity theory.

Perspectives In Computational Complexity

Author : Manindra Agrawal
ISBN : 9783319054469
Genre : Mathematics
File Size : 32. 63 MB
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This book brings together contributions by leading researchers in computational complexity theory written in honor of Somenath Biswas on the occasion of his sixtieth birthday. They discuss current trends and exciting developments in this flourishing area of research and offer fresh perspectives on various aspects of complexity theory. The topics covered include arithmetic circuit complexity, lower bounds and polynomial identity testing, the isomorphism conjecture, space-bounded computation, graph isomorphism, resolution and proof complexity, entropy and randomness. Several chapters have a tutorial flavor. The aim is to make recent research in these topics accessible to graduate students and senior undergraduates in computer science and mathematics. It can also be useful as a resource for teaching advanced level courses in computational complexity.

Computational Complexity Of Some Optimization Problems In Planning

Author : Meysam Aghighi
ISBN : 9789176855195
Genre :
File Size : 20. 30 MB
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Automated planning is known to be computationally hard in the general case. Propositional planning is PSPACE-complete and first-order planning is undecidable. One method for analyzing the computational complexity of planning is to study restricted subsets of planning instances, with the aim of differentiating instances with varying complexity. We use this methodology for studying the computational complexity of planning. Finding new tractable (i.e. polynomial-time solvable) problems has been a particularly important goal for researchers in the area. The reason behind this is not only to differentiate between easy and hard planning instances, but also to use polynomial-time solvable instances in order to construct better heuristic functions and improve planners. We identify a new class of tractable cost-optimal planning instances by restricting the causal graph. We study the computational complexity of oversubscription planning (such as the net-benefit problem) under various restrictions and reveal strong connections with classical planning. Inspired by this, we present a method for compiling oversubscription planning problems into the ordinary plan existence problem. We further study the parameterized complexity of cost-optimal and net-benefit planning under the same restrictions and show that the choice of numeric domain for the action costs has a great impact on the parameterized complexity. We finally consider the parameterized complexity of certain problems related to partial-order planning. In some applications, less restricted plans than total-order plans are needed. Therefore, a partial-order plan is being used instead. When dealing with partial-order plans, one important question is how to achieve optimal partial order plans, i.e. having the highest degree of freedom according to some notion of flexibility. We study several optimization problems for partial-order plans, such as finding a minimum deordering or reordering, and finding the minimum parallel execution length.

Theory Of Computational Complexity

Author : Ding-Zhu Du
ISBN : 9781118594971
Genre : Mathematics
File Size : 42. 9 MB
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Praise for the First Edition "...complete, up-to-date coverage of computational complexity theory...the book promises to become the standard reference on computational complexity." -Zentralblatt MATH A thorough revision based on advances in the field of computational complexity and readers’ feedback, the Second Edition of Theory of Computational Complexity presents updates to the principles and applications essential to understanding modern computational complexity theory. The new edition continues to serve as a comprehensive resource on the use of software and computational approaches for solving algorithmic problems and the related difficulties that can be encountered. Maintaining extensive and detailed coverage, Theory of Computational Complexity, Second Edition, examines the theory and methods behind complexity theory, such as computational models, decision tree complexity, circuit complexity, and probabilistic complexity. The Second Edition also features recent developments on areas such as NP-completeness theory, as well as: A new combinatorial proof of the PCP theorem based on the notion of expander graphs, a research area in the field of computer science Additional exercises at varying levels of difficulty to further test comprehension of the presented material End-of-chapter literature reviews that summarize each topic and offer additional sources for further study Theory of Computational Complexity, Second Edition, is an excellent textbook for courses on computational theory and complexity at the graduate level. The book is also a useful reference for practitioners in the fields of computer science, engineering, and mathematics who utilize state-of-the-art software and computational methods to conduct research. A thorough revision based on advances in the field of computational complexity and readers’ feedback, the Second Edition of Theory of Computational Complexity presents updates to the principles and applications essential to understanding modern computational complexity theory. The new edition continues to serve as a comprehensive resource on the use of software and computational approaches for solving algorithmic problems and the related difficulties that can be encountered. Maintaining extensive and detailed coverage, Theory of Computational Complexity, Second Edition, examines the theory and methods behind complexity theory, such as computational models, decision tree complexity, circuit complexity, and probabilistic complexity. The Second Edition also features recent developments on areas such as NP-completeness theory, as well as: • A new combinatorial proof of the PCP theorem based on the notion of expander graphs, a research area in the field of computer science • Additional exercises at varying levels of difficulty to further test comprehension of the presented material • End-of-chapter literature reviews that summarize each topic and offer additional sources for further study Theory of Computational Complexity, Second Edition, is an excellent textbook for courses on computational theory and complexity at the graduate level. The book is also a useful reference for practitioners in the fields of computer science, engineering, and mathematics who utilize state-of-the-art software and computational methods to conduct research.

Formal Languages Automata And Numeration Systems

Author : Michel Rigo
ISBN : 9781119008224
Genre : Computers
File Size : 34. 55 MB
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Formal Languages, Automaton and Numeration Systems presents readers with a review of research related to formal language theory, combinatorics on words or numeration systems, such as Words, DLT (Developments in Language Theory), ICALP, MFCS (Mathematical Foundation of Computer Science), Mons Theoretical Computer Science Days, Numeration, CANT (Combinatorics, Automata and Number Theory). Combinatorics on words deals with problems that can be stated in a non-commutative monoid, such as subword complexity of finite or infinite words, construction and properties of infinite words, unavoidable regularities or patterns. When considering some numeration systems, any integer can be represented as a finite word over an alphabet of digits. This simple observation leads to the study of the relationship between the arithmetical properties of the integers and the syntactical properties of the corresponding representations. One of the most profound results in this direction is given by the celebrated theorem by Cobham. Surprisingly, a recent extension of this result to complex numbers led to the famous Four Exponentials Conjecture. This is just one example of the fruitful relationship between formal language theory (including the theory of automata) and number theory. Contents to include: • algebraic structures, homomorphisms, relations, free monoid • finite words, prefixes, suffixes, factors, palindromes • periodicity and Fine–Wilf theorem • infinite words are sequences over a finite alphabet • properties of an ultrametric distance, example of the p-adic norm • topology of the set of infinite words • converging sequences of infinite and finite words, compactness argument • iterated morphism, coding, substitutive or morphic words • the typical example of the Thue–Morse word • the Fibonacci word, the Mex operator, the n-bonacci words • wordscomingfromnumbertheory(baseexpansions,continuedfractions,...) • the taxonomy of Lindenmayer systems • S-adic sequences, Kolakoski word • repetition in words, avoiding repetition, repetition threshold • (complete) de Bruijn graphs • concepts from computability theory and decidability issues • Post correspondence problem and application to mortality of matrices • origins of combinatorics on words • bibliographic notes • languages of finite words, regular languages • factorial, prefix/suffix closed languages, trees and codes • unambiguous and deterministic automata, Kleene’s theorem • growth function of regular languages • non-deterministic automata and determinization • radix order, first word of each length and decimation of a regular language • the theory of the minimal automata • an introduction to algebraic automata theory, the syntactic monoid and the syntactic complexity • star-free languages and a theorem of Schu ̈tzenberger • rational formal series and weighted automata • context-free languages, pushdown automata and grammars • growth function of context-free languages, Parikh’s theorem • some decidable and undecidable problems in formal language theory • bibliographic notes • factor complexity, Morse–Hedlund theorem • arithmetic complexity, Van Der Waerden theorem, pattern complexity • recurrence, uniform recurrence, return words • Sturmian words, coding of rotations, Kronecker’s theorem • frequencies of letters, factors and primitive morphism • critical exponent • factor complexity of automatic sequences • factor complexity of purely morphic sequences • primitive words, conjugacy, Lyndon word • abelianisation and abelian complexity • bibliographic notes • automatic sequences, equivalent definitions • a theorem of Cobham, equivalence of automatic sequences with constant length morphic sequences • a few examples of well-known automatic sequences • about Derksen’s theorem • some morphic sequences are not automatic • abstract numeration system and S-automatic sequences • k − ∞-automatic sequences • bibliographic notes • numeration systems, greedy algorithm • positional numeration systems, recognizable sets of integers • divisibility criterion and recognizability of N • properties of k-recognizable sets of integers, ratio and difference of consec- utive elements: syndeticity • integer base and Cobham’s theorem on the base dependence of the recog- nizability • non-standard numeration systems based on sequence of integers • linear recurrent sequences, Loraud and Hollander results • Frougny’s normalization result and addition • morphic numeration systems/sets of integers whose characteristic sequence is morphic • towards a generalization of Cobham’s theorem • a few words on the representation of real numbers, β-integers, finiteness properties • automata associated with Parry numbers and numeration systems • bibliographic notes First order logic • Presburger arithmetic and decidable theory • Muchnik’s characterization of semi-linear sets • Bu ̈chi’s theorem: k-recognizable sets are k-definable • extension to Pisot numeration systems • extension to real numbers • decidability issues for numeration systems • applications in combinatorics on words

Statistical Computing In C And R

Author : Randall L. Eubank
ISBN : 9781466515376
Genre : Mathematics
File Size : 51. 71 MB
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With the advancement of statistical methodology inextricably linked to the use of computers, new methodological ideas must be translated into usable code and then numerically evaluated relative to competing procedures. In response to this, Statistical Computing in C++ and R concentrates on the writing of code rather than the development and study of numerical algorithms per se. The book discusses code development in C++ and R and the use of these symbiotic languages in unison. It emphasizes that each offers distinct features that, when used in tandem, can take code writing beyond what can be obtained from either language alone. The text begins with some basics of object-oriented languages, followed by a "boot-camp" on the use of C++ and R. The authors then discuss code development for the solution of specific computational problems that are relevant to statistics including optimization, numerical linear algebra, and random number generation. Later chapters introduce abstract data structures (ADTs) and parallel computing concepts. The appendices cover R and UNIX Shell programming. Features Includes numerous student exercises ranging from elementary to challenging Integrates both C++ and R for the solution of statistical computing problems Uses C++ code in R and R functions in C++ programs Provides downloadable programs, available from the authors’ website The translation of a mathematical problem into its computational analog (or analogs) is a skill that must be learned, like any other, by actively solving relevant problems. The text reveals the basic principles of algorithmic thinking essential to the modern statistician as well as the fundamental skill of communicating with a computer through the use of the computer languages C++ and R. The book lays the foundation for original code development in a research environment.

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