73,99 € *

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Stand: 16.09.2019 Zum Angebot

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77,99 € *

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Gain a clear understanding of even the most complex, highly theoretical computational theory topics in the approachable presentation found only in the market-leading INTRODUCTION TO THE THEORY OF COMPUTATION, 3E. The number one choice for today´s computational theory course, this revision continues the book´s well-know, approachable style with timely revisions, additional practice, and more memorable examples in key areas. A new first-of-its-kind theoretical treatment of deterministic context-free languages is ideal for a better understanding of parsing and LR(k) grammars. You gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs. INTRODUCTION TO THE THEORY OF COMPUTATION, 3E´s comprehensive coverage makes this a valuable reference for your continued studies in theoretical computing.

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Stand: 10.09.2019 Zum Angebot

Stand: 10.09.2019 Zum Angebot

53,99 € *

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The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject

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Stand: 10.09.2019 Zum Angebot

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86,99 € *

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Stand: 10.09.2019 Zum Angebot

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60,99 € *

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The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy). This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes. A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The book´s main aims are: * To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriate * To introduce the main issues surrounding the design of intelligent agents * To introduce the main issues surrounding the design of a multi-agent society * To introduce a number of typical applications for agent technology After reading the book the student should understand: * The notion of an agent, how agents are distinct from other software paradigms (e.g. objects) and the characteristics of applications that lend themselves to agent-oriented software * The key issues associated with constructing agents capable of intelligent autonomous action and the main approaches taken to developing such agents * The key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems * The main application areas of agent-based systems

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Stand: 06.09.2019 Zum Angebot

Stand: 06.09.2019 Zum Angebot

51,99 € *

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Despite growing interest in the mathematical analysis of algorithms, basic information on methods and models has rarely been directly accessible to practitioners, researchers, or students. This book organizes and presents that knowledge, fully introducing today´s primary techniques for mathematically analyzing algorithms. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematical and computer science material, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They focus on ´´average-case´´ or ´´probabilistic´´ analysis, while also covering tools for ´´worst case´´ or ´´complexity´´ analysis. Improvements in this edition include: * Upgraded figures and code * Newer style for presenting much of the text´s math * An all-new chapter on trees This book´s thorough, self-contained coverage will help readers appreciate the field´s challenges, prepare them for advanced results covered in Donald Knuth´s books, and provide the background they need to keep abreast of new research. Coverage includes: recurrences, generating functions, asymptotics, trees, strings, maps, sorting, tree search, string search, and hashing algorithms. Ideal for junior- or senior-level courses on mathematical analysis of algorithms, this book will also be useful in courses on discrete mathematics for computer scientists, and in introducing mathematics students to computer science principles related to algorithms and data structures. Product Description Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Authors Robert Sedgewick and the late Philippe Flajolet emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Improvements and additions in this new edition include upgraded figures and code, an all-new chapter introducing analytic combinatorics, and simplified derivations via analytic combinatorics throughout. The book´s thorough, self-contained coverage will help readers appreciate the field´s challenges and prepare them for advanced study.

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Stand: 15.09.2019 Zum Angebot

Stand: 15.09.2019 Zum Angebot

29,99 € *

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A project-based guide to the basics of deep learning.

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Stand: 08.09.2019 Zum Angebot

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89,99 € *

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Stand: 06.09.2019 Zum Angebot

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40,99 € *

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Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles.

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Stand: 06.09.2019 Zum Angebot

Stand: 06.09.2019 Zum Angebot