Artificial Intelligence Methods in Intelligent Algorithms, Radek Silhavy
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.
Описание: A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the ""average."" From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendency models based on the Gaussian distribution are a seemingly natural and obvious choice for modeling sensory data. However, insights from neuroscience, psychology, and computer vision suggest an alternate strategy: preferentially focusing representational resources on the extremes of the distribution of sensory inputs. The notion of treating extrema near a decision boundary as features is not necessarily new, but a comprehensive statistical theory of recognition based on extrema is only now just emerging in the computer vision literature. This book begins by introducing the statistical Extreme Value Theory (EVT) for visual recognition. In contrast to central-tendency modeling, it is hypothesized that distributions near decision boundaries form a more powerful model for recognition tasks by focusing coding resources on data that are arguably the most diagnostic features. EVT has several important properties: strong statistical grounding, better modeling accuracy near decision boundaries than Gaussian modeling, the ability to model asymmetric decision boundaries, and accurate prediction of the probability of an event beyond our experience. The second part of the book uses the theory to describe a new class of machine learning algorithms for decision making that are a measurable advance beyond the state-of-the-art. This includes methods for post-recognition score analysis, information fusion, multi-attribute spaces, and calibration of supervised machine learning algorithms.
Описание: This book presents the latest trends and approaches in artificial intelligence research and its application to intelligent systems. It discusses hybridization of algorithms, new trends in neural networks, optimisation algorithms and real-life issues related to the application of artificial methods. The book constitutes the second volume of the refereed proceedings of the Artificial Intelligence and Algorithms in Intelligent Systems of the 7th Computer Science On-line Conference 2018 (CSOC 2018), held online in April 2018.
Описание: Although recommendation systems have become a vital research area in the fields of cognitive science, approximation theory, information retrieval and management sciences, they still require improvements to make recommendation methods more effective and intelligent. <br><br><em>Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods</em> is a comprehensive collection of research on the latest advancements of intelligence techniques and their application to recommendation systems and how this could improve this field of study.
Автор: Li, Fanzhang / Zhang, Li / Zhang, Zhao Название: Dynamic Fuzzy Machine Learning ISBN: 3110518708 ISBN-13(EAN): 9783110518702 Издательство: Walter de Gruyter Рейтинг: Цена: 22439.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.
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.
Автор: Li Название: Artificial Intelligence with Uncertainty ISBN: 1584889985 ISBN-13(EAN): 9781584889984 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Поставка под заказ.
Описание: Through mathematical theories, models, and experimental computations, this book explores the uncertainties of knowledge and intelligence that occur during the cognitive processes of human beings. It describes the cloud model, its uncertainties of randomness and fuzziness, and the correlation between them. The book also centers on other physical methods for data mining, such as the data field and knowledge discovery state space. In addition, it presents an inverted pendulum example to discuss reasoning and control with uncertain knowledge as well as provides a cognitive physics model to visualize human thinking with hierarchy.
Описание: Constitutes the refereed proceedings of the First International Conference on Intelligent Robotics and Applications, ICIRA 2008, held in Wuhan, China, in October 2008. This book includes such topics as robot control, cognitive robotics, rehabilitation robotics, health care and artificial limb, robot learning, and robot vision.
Описание: This two volume set LNAI 8102 and LNAI 8103 constitutes the refereed proceedings of the 6th International Conference on Intelligent Robotics and Applications, ICIRA 2013, held in Busan, South Korea, in September 2013.
Описание: Second International Conference ICIRA 2009 Singapore December 1618 2009 Proceedings. .
Автор: Liu Derong, Apippi Cesare, Zhao Dongbin Название: Frontiers of Intelligent Control and Information Processing ISBN: 9814616877 ISBN-13(EAN): 9789814616874 Издательство: World Scientific Publishing Цена: 23760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The current research and development in intelligent control and information processing have been driven increasingly by advancements made from fields outside the traditional control areas, into new frontiers of intelligent control and information processing so as to deal with ever more complex systems with ever growing size of data and complexity.
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.
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