General Video Game Artificial Intelligence, Diego Perez Liebana, Simon M. Lucas, Raluca D. Gaina, Julian Togelius, Ahmed Khalifa, Jialin Liu
Автор: Millington, Ian, Funge, John Название: Artificial Intelligence for Games ISBN: 0123747317 ISBN-13(EAN): 9780123747310 Издательство: Taylor&Francis Рейтинг: Цена: 10870.00 р. Наличие на складе: Поставка под заказ.
Описание: Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional experience to the problem of improving the quality of AI in games. He describes numerous examples from real games and explores the underlying ideas through detailed case studies. He goes further to introduce many techniques little used by developers today. The book's associated web site contains a library of C++ source code and demonstration programs, and a complete commercial source code library of AI algorithms and techniques.<br><br>"Artificial Intelligence for Games - 2nd edition" will be highly useful to academics teaching courses on game AI, in that it includes exercises with each chapter. It will also include new and expanded coverage of the following: AI-oriented gameplay; Behavior driven AI; Casual games (puzzle games). <br><br>* The first comprehensive, professional tutorial and reference to implement true AI in games written by an engineer with extensive industry experience.<br>* Walks through the entire development process from beginning to end.<br>* Includes examples from over 100 real games, 10 in-depth case studies, and web site with sample code.
Автор: Diego Perez Liebana, Simon M. Lucas, Raluca D. Gaina, Julian Togelius, Ahmed Khalifa, Jialin Liu Название: General Video Game Artificial Intelligence ISBN: 1681736446 ISBN-13(EAN): 9781681736440 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11642.00 р. Наличие на складе: Нет в наличии.
Описание: Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors during these years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.
Автор: J.-J. Ch. Meyer, W. van der Hoek Название: Epistemic Logic for AI and Computer Science ISBN: 0521602807 ISBN-13(EAN): 9780521602808 Издательство: Cambridge Academ Рейтинг: Цена: 9186.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, based on courses taught at universities and summer schools, provides a broad introduction to the subject; many exercises are included with their solutions.
Автор: Boden, Margaret A. (research Professor Of Cognitive Science, University Of Sussex) Название: Artificial intelligence: a very short introduction ISBN: 0199602913 ISBN-13(EAN): 9780199602919 Издательство: Oxford Academ Рейтинг: Цена: 1582.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This concise guide explains the history, theory, potential, application, and limitations of Artificial Intelligence. Boden shows how research into AI has shed light on the working of human and animal minds, and she considers the philosophical challenges AI raises: could programs ever be really intelligent, creative or even conscious?
Автор: George, Michael L., Название: Lean six sigma in the age of artificial intelligence : ISBN: 1260135039 ISBN-13(EAN): 9781260135039 Издательство: McGraw-Hill Рейтинг: Цена: 5318.00 р. Наличие на складе: Поставка под заказ.
Описание: The world's leading expert on Lean Six Sigma provides the missing link for reducing waste and taking operations to the next level: Artificial IntelligenceLean Six Sigma (LSS) has been helping companies improve their processes since 2001-but as yet, no one has taken this revolutionary management approach to its limits. Now, The Fourth Revolution in Manufacturing shows exactly how to do that-by adding artificial intelligence (AI) to the mix. This game-changing guide takes you through the process of using AI to unlock maximum speed, solve complex manufacturing challenges, reduce waste, increase company profits, and ultimately beat the competition.
Breakthrough Manufacturing explains how to:* Unlock your company's full potential with the AI + LSS approach* Utilize the AI + LSS three-step process to dramatically improve profits * Apply AI + LSS to engineering and other non-manufacturing processes* Harness the interaction of AI+LSS and the ERP system* Create a scorecard and measure your results
Learn how Artificial Intelligence (AI) is being applied in the fashion industry. With an application focused approach, this book provides real-world examples, breaks down technical jargon for non-technical readers, and provides an educational resource for fashion professionals. The book investigates the ways in which AI is impacting every part of the fashion value chain starting with product discovery and working backwards to manufacturing.
Artificial Intelligence for Fashion walks you through concepts, such as connected retail, data mining, and artificially intelligent robotics. Each chapter contains an example of how AI is being applied in the fashion industry illustrated by one major technological theme. There are no equations, algorithms, or code. The technological explanations are cumulative so you'll discover more information about the inner workings of artificial intelligence in practical stages as the book progresses.
What You'll Learn
Gain a basic understanding of AI and how it is used in fashion
Understand key terminology and concepts in AI
Review the new competitive landscape of the fashion industry
Conceptualize and develop new ways to apply AI within the workplace
Who This Book Is For Fashion industry professionals from designers, managers, department heads, and executives can use this book to learn about how AI is impacting roles in every department and profession.
Автор: Tian & Chen Название: Intelligent Image And Video Interpretation ISBN: 146663958X ISBN-13(EAN): 9781466639584 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 24116.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Due to increasing potential in real-world applications such as visual communications, computer assisted biomedical imaging, and video surveillance, image and video interpretations have become an area of growing interest. <em>Intelligent Image and Video Interpretation: Algorithms and Applications</em> covers all aspects of image and video analysis from low-level early visions to high-level recognition. This publication highlights how these techniques have become applicable and will prove to be a valuable tool for researchers, professionals, and graduate students working or studying the fields of imaging and video processing.
Описание: Presents current research relating to multimedia technologies including video and image restoration and enhancement as well as algorithms used for image and video compression, indexing and retrieval processes, and security concerns. It features insight from researchers from around the world.
Автор: Nie Liqiang, Liu Meng, Song Xuemeng Название: Multimodal Learning toward Micro-Video Understanding ISBN: 1681736306 ISBN-13(EAN): 9781681736303 Издательство: Mare Nostrum (Eurospan) Цена: 15523.00 р. Наличие на складе: Нет в наличии.
Описание:
Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.
Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.
Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.
In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
Автор: Nie Liqiang, Liu Meng, Song Xuemeng Название: Multimodal Learning toward Micro-Video Understanding ISBN: 1681736284 ISBN-13(EAN): 9781681736280 Издательство: Mare Nostrum (Eurospan) Цена: 12335.00 р. Наличие на складе: Нет в наличии.
Описание:
Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.
Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.
Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.
In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel and Amazon can be interpreted using this book.
Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN)
Authored by top experts, global field pioneers and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making
Edited by high-level academics and researchers in intelligent systems and neural networks
Описание: Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.
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