Author: Marek Cygan
Publisher: Springer
ISBN: 3319212753
Category : Computers
Languages : en
Pages : 613
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Book Description
This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way. The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds. All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.
Author: Rolf Niedermeier
Publisher: OUP Oxford
ISBN: 0191524158
Category : Mathematics
Languages : en
Pages : 316
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Book Description
This research-level text is an application-oriented introduction to the growing and highly topical area of the development and analysis of efficient fixed-parameter algorithms for optimally solving computationally hard combinatorial problems. The book is divided into three parts: a broad introduction that provides the general philosophy and motivation; followed by coverage of algorithmic methods developed over the years in fixed-parameter algorithmics forming the core of the book; and a discussion of the essentials from parameterized hardness theory with a focus on W[1]-hardness which parallels NP-hardness, then stating some relations to polynomial-time approximation algorithms, and finishing up with a list of selected case studies to show the wide range of applicability of the presented methodology. Aimed at graduate and research mathematicians, programmers, algorithm designers, and computer scientists, the book introduces the basic techniques and results and provides a fresh view on this highly innovative field of algorithmic research.
Author: J. Flum
Publisher: Springer Science & Business Media
ISBN: 354029953X
Category : Computers
Languages : en
Pages : 494
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Book Description
This book is a state-of-the-art introduction into both algorithmic techniques for fixed-parameter tractability and the structural theory of parameterized complexity classes. It presents detailed proofs of recent advanced results that have not appeared in book form before and replaces the earlier publication "Parameterized Complexity" by Downey and Fellows as the definitive book on this subject. The book will interest computer scientists, mathematicians and graduate students engaged with algorithms and problem complexity.
Author: Rodney G. Downey
Publisher: Springer Science & Business Media
ISBN: 1461205158
Category : Computers
Languages : en
Pages : 538
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Book Description
An approach to complexity theory which offers a means of analysing algorithms in terms of their tractability. The authors consider the problem in terms of parameterized languages and taking "k-slices" of the language, thus introducing readers to new classes of algorithms which may be analysed more precisely than was the case until now. The book is as self-contained as possible and includes a great deal of background material. As a result, computer scientists, mathematicians, and graduate students interested in the design and analysis of algorithms will find much of interest.
Author: F.J. Lobo
Publisher: Springer
ISBN: 3540694323
Category : Technology & Engineering
Languages : en
Pages : 318
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Book Description
One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.
Author: Tim Roughgarden
Publisher: Cambridge University Press
ISBN: 1108494315
Category : Computers
Languages : en
Pages : 705
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Book Description
Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.
Author: Fedor V. Fomin
Publisher: Cambridge University Press
ISBN: 1107057760
Category : Computers
Languages : en
Pages : 531
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Book Description
A complete introduction to recent advances in preprocessing analysis, or kernelization, with extensive examples using a single data set.
Author: Prosenjit Bose
Publisher: Springer Science & Business Media
ISBN: 3540001425
Category : Mathematics
Languages : en
Pages : 668
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Book Description
This book constitutes the refereed proceedings of the 13th Annual International Symposium on Algorithms and Computation, ISAAC 2002, held in Vancouver, BC, Canada in November 2002. The 54 revised full papers presented together with 3 invited contributions were carefully reviewed and selected from close to 160 submissions. The papers cover all relevant topics in algorithmics and computation, in particular computational geometry, algorithms and data structures, approximation algorithms, randomized algorithms, graph drawing and graph algorithms, combinatorial optimization, computational biology, computational finance, cryptography, and parallel and distributedd algorithms.
Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262047012
Category : Computers
Languages : en
Pages : 701
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Book Description
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.
Author: Zhao Zhang
Publisher: Springer
ISBN: 9783030576011
Category : Computers
Languages : en
Pages : 0
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Book Description
This volume constitutes the proceedings of the 14th International Conference on Algorithmic Aspects in Information and Management, AAIM 2020, held in Jinhua, China in August 2020. The 39 full papers and 17 short papers presented were carefully reviewed and selected from 76 submissions. The papers deal with emerging important algorithmic problems with a focus on the fundamental background, theoretical technology development, and real-world applications associated with information and management analysis, modeling and data mining. Special considerations are given to algorithmic research that was motivated by real-world applications.
