Author: Arnaldo Pérez CastañoPublish On: 2018-05-23
This book explores subjects such as neural networks, agents, multi agent systems, supervised learning, and unsupervised learning.
Author: Arnaldo Pérez Castaño
Discover how all levels Artificial Intelligence (AI) can be present in the most unimaginable scenarios of ordinary lives. This book explores subjects such as neural networks, agents, multi agent systems, supervised learning, and unsupervised learning. These and other topics will be addressed with real world examples, so you can learn fundamental concepts with AI solutions and apply them to your own projects. People tend to talk about AI as something mystical and unrelated to their ordinary life. Practical Artificial Intelligence provides simple explanations and hands on instructions. Rather than focusing on theory and overly scientific language, this book will enable practitioners of all levels to not only learn about AI but implement its practical uses. What You’ll Learn Understand agents and multi agents and how they are incorporated Relate machine learning to real-world problems and see what it means to you Apply supervised and unsupervised learning techniques and methods in the real world Implement reinforcement learning, game programming, simulation, and neural networks Who This Book Is For Computer science students, professionals, and hobbyists interested in AI and its applications.
Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe.
Author: Bernard Marr
Publisher: John Wiley & Sons
Category: Business & Economics
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
Featuring contributions from leading experts and thinkers in the theory of artificial intelligence (AI), this is one of the first books dedicated to examining the risks of AI. The book evaluates predictions of the future of AI, proposes ...
Author: Vincent C. Müller
Publisher: CRC Press
Featuring contributions from leading experts and thinkers in the theory of artificial intelligence (AI), this is one of the first books dedicated to examining the risks of AI. The book evaluates predictions of the future of AI, proposes ways to ensure that AI systems will be beneficial to humans, and then critically evaluates such proposals. The
This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications.
Author: Ameet V Joshi
Publisher: Springer Nature
Category: Technology & Engineering
This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals. It makes minimal use of mathematics to make the topics more intuitive and accessible. Presents a full reference to artificial intelligence and machine learning techniques - in theory and application; Provides a guide to AI and ML with minimal use of mathematics to make the topics more intuitive and accessible; Connects all ML and AI techniques to applications and introduces implementations.
Author: Constantinos KoutsojannisPublish On: 2009-01-17
The objective of the workshop was to bring together scientists, engineers and practitioners, who work on designing or developing applications that use intelligent techniques or work on intelligent techniques and apply them to application ...
Author: Constantinos Koutsojannis
Publisher: Springer Science & Business Media
In recent years, the use of Artificial Intelligence (AI) techniques has been greatly increased. The term “intelligence” seems to be a “must” in a large number of European and International project calls. AI Techniques have been used in almost any domain. Application-oriented systems usually incorporate some kind of “intelligence” by using techniques stemming from intelligent search, knowledge representation, machine learning, knowledge discovery, intelligent agents, computational intelligence etc. The Workshop on “Applications with Artificial Intelligence” seeks for quality papers on computer applications that incorporate some kind of AI technique. The objective of the workshop was to bring together scientists, engineers and practitioners, who work on designing or developing applications that use intelligent techniques or work on intelligent techniques and apply them to application domains (like medicine, biology, education etc), to present and discuss their research works and exchange ideas in this book.
This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments.
Author: William F. Lawless
Publisher: Springer Nature
Category: Artificial intelligence
This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams' here the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.
Author: Georgios N. YannakakisPublish On: 2018-02-17
This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games.
Author: Georgios N. Yannakakis
This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading.
This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers.
Author: Dario Floreano
Publisher: MIT Press
A comprehensive introduction to new approaches in artificial intelligence and robotics that are inspired by self-organizing biological processes and structures. New approaches to artificial intelligence spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development, and learning. Traditionally, artificial intelligence has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wider range of biological structures that that are capable of autonomous self-organization. Examples of these new approaches include evolutionary computation and evolutionary electronics, artificial neural networks, immune systems, biorobotics, and swarm intelligence—to mention only a few. This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers. Each chapter presents computational approaches inspired by a different biological system; each begins with background information about the biological system and then proceeds to develop computational models that make use of biological concepts. The chapters cover evolutionary computation and electronics; cellular systems; neural systems, including neuromorphic engineering; developmental systems; immune systems; behavioral systems—including several approaches to robotics, including behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and collective systems, including swarm robotics as well as cooperative and competitive co-evolving systems. Chapters end with a concluding overview and suggested reading.
In R.Michalski, J.Carbonell, T.Mitchell, eds., Machine Learning II: An Artificial Intelligence Approach. Los Altos, CA: Morgan Kaufmann. Bergadano, F. und Giordana, A. (1988). A Knowledge-Intensive Approach to Concept Induction.
Author: Johannes Retti
Publisher: Springer Science & Business Media
Die 5. Österreichische Artificial-Intelligence-Tagung setzt sich zusammen aus wissenschaftlichem Programm, Workshops und Tutorials. Der wissenschaftlich orientierte Teil des Tagungsprogramms umfa€t sowohl eingeladene als auch begutachtete Vorträge zu den Themen Qualitatives Schlie€en, Methodik Wissensbasierter Systeme und deren Anwendung, Logik/Deduktion, Natürlichsprachliche Systeme, Lernen und Kognition. Zum Informationsaustausch waren zusätzlich Workshops zur Weiterbildung vorgesehen. Besonders das Thema "Philosophie und KI" demonstrierte das allgemeine Interesse. Dies soll mit Beiträgen dokumentiert werden, die einen Überblick über Berührungspunkte der KI mit philosophischen Strömungen bieten und auch den Einflu€ der KI als Teil der Informatik auf das philosophische Weltbild verdeutlichen. Ebenfalls repräsentative Beiträge wurden zu den Workshops "Konnektionismus", "Qualitatives Schlie€en" und "Begriffsbildung/-modellierung" ausgewählt.