Knowing our World: An Artificial Intelligence Perspective, Luger, George F.
Автор: Peter Norvig Название: Paradigms of Artificial Intelligence Programming, ISBN: 1558601910 ISBN-13(EAN): 9781558601918 Издательство: Elsevier Science Рейтинг: Цена: 9599.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Paradigms of AI Programming teaches advanced Common Lisp techniques in the context of building major AI systems.
The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts and methodologies adopted in dependability analysis, the book discusses the main features of PGM formalisms (like Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model languages.
Methodologies for deriving PGMs from standard dependability formalisms will be introduced, by pointing out tools able to support such a process. Several case studies will be presented and analyzed to support the suitability of the use of PGMs in the study of dependable systems.
Автор: Hans W. Guesgen; Joachim Hertzberg Название: A Perspective of Constraint-Based Reasoning ISBN: 3540555102 ISBN-13(EAN): 9783540555100 Издательство: Springer Рейтинг: Цена: 4890.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Examining constraint satisfaction, this monograph presents all approaches under a common, generalizing view: dynamic constraints. It aims to provide insights about the different approaches, and to form a practical basis for teaching constraint-based reasoning.
Автор: Andrew Ortony; Jon Slack; Oliviero Stock Название: Communication from an Artificial Intelligence Perspective ISBN: 3540558810 ISBN-13(EAN): 9783540558811 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the question of how current computational approaches to communication can accommodate the complexities of human-human and human-machine communication. It is based on a NATO workshop.
Автор: Krzysztof R. Apt; Victor W. Marek; Mirek Truszczyn Название: The Logic Programming Paradigm ISBN: 3642642497 ISBN-13(EAN): 9783642642494 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: They address such diverse topics as: computational molecular biology, machine learning, mobile computing, multi-agent systems, planning, numerical computing and dynamical systems, database systems, an alternative to the "formulas as types" approach, program semantics and analysis, and natural language processing.
Описание: This book addresses the issue of cognitive semantics` aspects that cannot be represented by traditional digital and logical means. The electromagnetic waves, quantum fields, beam of light, chaos control, relativistic theory, cosmic string recognition, category theory, group theory, and so on can be used for this aim.
Описание: This book discusses the advancements in artificial intelligent techniques used in the well-being of human healthcare. The edited book is divided into four parts - part A discusses introduction to artificial intelligence and machine learning in healthcare; part B highlights different analytical techniques used in healthcare;
Описание: This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) - Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing.
Автор: Max Bramer Название: Artificial Intelligence. An International Perspective ISBN: 3642032257 ISBN-13(EAN): 9783642032257 Издательство: Springer Рейтинг: Цена: 10195.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Featuring the viewpoint of expert members of the IFIP Technical Committee 12, its Working Groups and their colleagues, this book provides an international perspective on recent and future directions in this significant field.
Описание: Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together.
A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets.
Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence--enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and scienceExplains how to apply common computational models and state-of-the-art architectures to process Big Data tasksDiscusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.
Описание: This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) - Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing.
