Algorithms, Humans, and Interactions, Shin, Don Donghee (Zayed University, UAE)
Автор: Cormen, Thomas H. Название: Introduction to Algorithms 4E ISBN: 026204630X ISBN-13(EAN): 9780262046305 Издательство: MIT Press Рейтинг: Цена: 25394.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A comprehensive update of a widely used textbook, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Since the publication of the first edition, Introduction to Algorithms has become a widely used text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout, with new chapters on matchings in bipartite graphs, online algorithms, and machine learning, and new material on such topics as solving recurrence equations, hash tables, potential functions, and suffix arrays. Each chapter is relatively self-contained, presenting an algorithm, a design technique, an application area, or a related topic, and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The fourth edition has 140 new exercises and 22 new problems, and color has been added to improve visual presentations. The writing has been revised throughout, and made clearer, more personal, and gender neutral. The book's website offers supplemental material.
Автор: Cormen, Thomas H., E Название: Introduction to algorithms 3 ed. ISBN: 0262033844 ISBN-13(EAN): 9780262033848 Издательство: MIT Press Рейтинг: Цена: 27588.00 р. Наличие на складе: Нет в наличии.
Описание: A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-base flow.
A riveting account of espionage for the digital age, from one of America's leading intelligence experts
Spying has never been more ubiquitous-or less understood. The world is drowning in spy movies, TV shows, and novels, but universities offer more courses on rock and roll than on the CIA and there are more congressional experts on powdered milk than espionage. This crisis in intelligence education is distorting public opinion, fueling conspiracy theories, and hurting intelligence policy. In Spies, Lies, and Algorithms, Amy Zegart separates fact from fiction as she offers an engaging and enlightening account of the past, present, and future of American espionage as it faces a revolution driven by digital technology. Drawing on decades of research and hundreds of interviews with intelligence officials, Zegart provides a history of U.S. espionage, from George Washington's Revolutionary War spies to today's spy satellites; examines how fictional spies are influencing real officials; gives an overview of intelligence basics and life inside America's intelligence agencies; explains the deadly cognitive biases that can mislead analysts; and explores the vexed issues of traitors, covert action, and congressional oversight. Most of all, Zegart describes how technology is empowering new enemies and opportunities, and creating powerful new players, such as private citizens who are successfully tracking nuclear threats using little more than Google Earth. And she shows why cyberspace is, in many ways, the ultimate cloak-and-dagger battleground, where nefarious actors employ deception, subterfuge, and advanced technology for theft, espionage, and information warfare. A fascinating and revealing account of espionage for the digital age, Spies, Lies, and Algorithms is essential reading for anyone who wants to understand the reality of spying today.
Автор: Kochenderfer Mykel J., Wheeler Tim A. Название: Algorithms for Optimization ISBN: 0262039427 ISBN-13(EAN): 9780262039420 Издательство: MIT Press Рейтинг: Цена: 14390.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.
This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language.
Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.
Автор: Chattamvelli Rajan, Shanmugam Ramalingam Название: Generating Functions in Engineering and the Applied Sciences ISBN: 1681736381 ISBN-13(EAN): 9781681736389 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 6930.00 р. Наличие на складе: Нет в наличии.
Описание:
This is an introductory book on generating functions (GFs) and their applications.
It discusses commonly encountered generating functions in engineering and applied sciences, such as ordinary generating functions (OGF), exponential generating functions (EGF), probability generating functions (PGF), etc. Some new GFs like Pochhammer generating functions for both rising and falling factorials are introduced in Chapter 2. Two novel GFs called "mean deviation generating function" (MDGF) and "survival function generating function" (SFGF), are introduced in Chapter 3. The mean deviation of a variety of discrete distributions are derived using the MDGF. The last chapter discusses a large number of applications in various disciplines including algebra, analysis of algorithms, polymer chemistry, combinatorics, graph theory, number theory, reliability, epidemiology, bio-informatics, genetics, management, economics, and statistics.
Some background knowledge on GFs is often assumed for courses in analysis of algorithms, advanced data structures, digital signal processing (DSP), graph theory, etc. These are usually provided by either a course on "discrete mathematics" or "introduction to combinatorics." But, GFs are also used in automata theory, bio-informatics, differential equations, DSP, number theory, physical chemistry, reliability engineering, stochastic processes, and so on. Students of these courses may not have exposure to discrete mathematics or combinatorics. This book is written in such a way that even those who do not have prior knowledge can easily follow through the chapters, and apply the lessons learned in their respective disciplines. The purpose is to give a broad exposure to commonly used techniques of combinatorial mathematics, highlighting applications in a variety of disciplines.
Описание: This undergraduate textbook is a concise introduction to the basic toolbox of structures that allow efficient organization and retrieval of data, key algorithms for problems on graphs, and generic techniques for modeling, understanding, and solving algorithmic problems.
Описание: social connections, social changes, acceptance of IT and the social conditions affecting this acceptance, effects of IT on humans and in response changes of IT, structures of the society and the influence of IT on these structures, changes of metaphysics influenced by IT and the social context of a knowledge society.
Fourth book in a series that provides an accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Includes hints of solutions to all quizzes and problems, and a series of YouTube videos by the author accompanies the book. Part 4 covers algorithmic tools for tackling NP-hard problems (heuristic algorithms, local search, dynamic programming, MIP and SAT solvers) and techniques for quickly recognizing NP-hard problems in the wild.
Описание: Accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees).
Автор: Tim Roughgarden Название: Beyond the Worst-Case Analysis of Algorithms ISBN: 1108494315 ISBN-13(EAN): 9781108494311 Издательство: Cambridge Academ Рейтинг: Цена: 9187.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case analysis. The book introduces exciting new methods for assessing algorithm performance.
Experts from a range of disciplines explore how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other.
Humans are not limited to a fixed set of innate or preprogrammed tasks. We learn quickly through language and other forms of natural interaction, and we improve our performance and teach others what we have learned. Understanding the mechanisms that underlie the acquisition of new tasks through natural interaction is an ongoing challenge. Advances in artificial intelligence, cognitive science, and robotics are leading us to future systems with human-like capabilities. A huge gap exists, however, between the highly specialized niche capabilities of current machine learning systems and the generality, flexibility, and in situ robustness of human instruction and learning. Drawing on expertise from multiple disciplines, this Str ngmann Forum Report explores how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other.
The contributors consider functional knowledge requirements, the ontology of interactive task learning, and the representation of task knowledge at multiple levels of abstraction. They explore natural forms of interactions among humans as well as the use of interaction to teach robots and software agents new tasks in complex, dynamic environments. They discuss research challenges and opportunities, including ethical considerations, and make proposals to further understanding of interactive task learning and create new capabilities in assistive robotics, healthcare, education, training, and gaming.
Contributors Tony Belpaeme, Katrien Beuls, Maya Cakmak, Joyce Y. Chai, Franklin Chang, Ropafadzo Denga, Marc Destefano, Mark d'Inverno, Kenneth D. Forbus, Simon Garrod, Kevin A. Gluck, Wayne D. Gray, James Kirk, Kenneth R. Koedinger, Parisa Kordjamshidi, John E. Laird, Christian Lebiere, Stephen C. Levinson, Elena Lieven, John K. Lindstedt, Aaron Mininger, Tom Mitchell, Shiwali Mohan, Ana Paiva, Katerina Pastra, Peter Pirolli, Roussell Rahman, Charles Rich, Katharina J. Rohlfing, Paul S. Rosenbloom, Nele Russwinkel, Dario D. Salvucci, Matthew-Donald D. Sangster, Matthias Scheutz, Julie A. Shah, Candace L. Sidner, Catherine Sibert, Michael Spranger, Luc Steels, Suzanne Stevenson, Terrence C. Stewart, Arthur Still, Andrea Stocco, Niels Taatgen, Andrea L. Thomaz, J. Gregory Trafton, Han L. J. van der Maas, Paul Van Eecke, Kurt VanLehn, Anna-Lisa Vollmer, Janet Wiles, Robert E. Wray III, Matthew Yee-King
Описание: social connections, social changes, acceptance of IT and the social conditions affecting this acceptance, effects of IT on humans and in response changes of IT, structures of the society and the influence of IT on these structures, changes of metaphysics influenced by IT and the social context of a knowledge society.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
