Детальная информация

Название: How smart machines think
Авторы: Gerrish Sean
Другие авторы: Scott Kevin
Организация: IEEE Xplore (Online Service); MIT Press
Выходные сведения: Cambridge, Massachusetts London, England: MIT Press, 2018
Коллекция: Электронные книги зарубежных издательств; Общая коллекция
Тематика: Neural networks (Computer science); Machine learning; Artificial intelligence; Нейронные сети; Машинное обучение; Искусственный интеллект; MIT Press eBooks Library
УДК: 004.032.26; 004.85
Тип документа: Другой
Тип файла: Другой
Язык: Английский
Права доступа: Доступ по паролю из сети Интернет (чтение, печать)
Ключ записи: 8555403

Разрешенные действия: Посмотреть

Аннотация

The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM's Watson triumphed on Jeopardy over puny human brains, computer programs can be trained to play Atari games. But how do all these thingswork? In this book, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today's machines so smart. Gerrish outlines some of the key ideas that enable intelligent machines to perceive and interact with the world. He describes the software architecture that allows self-driving cars to stay on the road and to navigate crowded urban environments; the million-dollar Netflix competition for a better recommendation engine (which had an unexpected ending); and how programmers trained computers to perform certain behaviors by offering them treats, as if they were training a dog. He explains how artificial neural networks enable computers to perceive the world-and to play Atari video games better than humans. He explains Watson's famous victory on Jeopardy, and he looks at how computers play games, describing AlphaGo and Deep Blue, which beat reigning world champions at the strategy games of Go and chess. Computers have not yet mastered everything, however; Gerrish outlines the difficulties in creating intelligent agents that can successfully play video games like StarCraft that have evaded solution-at least for now.

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