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Systems Engineering and Artificial Intelligence

Systems Engineering and Artificial Intelligence PDF Author: William F. Lawless
Publisher: Springer Nature
ISBN: 3030772837
Category : Computers
Languages : en
Pages : 566

Book Description
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—where 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.

Systems Engineering and Artificial Intelligence

Systems Engineering and Artificial Intelligence PDF Author: William F. Lawless
Publisher: Springer Nature
ISBN: 3030772837
Category : Computers
Languages : en
Pages : 566

Book Description
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—where 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.

Machine Learning and Systems Engineering

Machine Learning and Systems Engineering PDF Author: Sio-Iong Ao
Publisher: Springer Science & Business Media
ISBN: 9048194199
Category : Technology & Engineering
Languages : en
Pages : 607

Book Description
A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October 20-22, 2009, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2009). Machine Learning and Systems Engineering contains forty-six revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Expert system, Intelligent decision making, Knowledge-based systems, Knowledge extraction, Data analysis tools, Computational biology, Optimization algorithms, Experiment designs, Complex system identification, Computational modeling, and industrial applications. Machine Learning and Systems Engineering offers the state of the art of tremendous advances in machine learning and systems engineering and also serves as an excellent reference text for researchers and graduate students, working on machine learning and systems engineering.

Applications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering PDF Author: Jingzheng Ren
Publisher: Elsevier
ISBN: 012821743X
Category : Technology & Engineering
Languages : en
Pages : 542

Book Description
Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering

Artificial Intelligence and Digital Systems Engineering

Artificial Intelligence and Digital Systems Engineering PDF Author: Adedeji B. Badiru
Publisher: CRC Press
ISBN: 1000472515
Category : Technology & Engineering
Languages : en
Pages : 128

Book Description
The resurgence of artificial intelligence has been fueled by the availability of the present generation of high-performance computational tools and techniques. This book is designed to provide introductory guidance to artificial intelligence, particularly from the perspective of digital systems engineering. Artificial Intelligence and Digital Systems Engineering provides a general introduction to the origin of AI and covers the wide application areas and software and hardware interfaces. It will prove to be instrumental in helping new users expand their knowledge horizon to the growing market of AI tools, as well as showing how AI is applicable to the development of games, simulation, and consumer products, particularly using artificial neural networks. This book is for the general reader, university students, and instructors of industrial, production, civil, mechanical, and manufacturing engineering. It will also be of interest to managers of technology, projects, business, plants, and operations.

Engineering Artificially Intelligent Systems

Engineering Artificially Intelligent Systems PDF Author: William F. Lawless
Publisher: Springer Nature
ISBN: 3030893855
Category : Computers
Languages : en
Pages : 291

Book Description
Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time. To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society. This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.

Intelligent Systems for Engineers and Scientists

Intelligent Systems for Engineers and Scientists PDF Author: Adrian A. Hopgood
Publisher: CRC Press
ISBN: 1466516178
Category : Computers
Languages : en
Pages : 455

Book Description
The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance. Check out the significantly expanded set of free web-based resources that support the book at: http://www.adrianhopgood.com/aitoolkit/

Artificial Intelligence and Evolutionary Computations in Engineering Systems

Artificial Intelligence and Evolutionary Computations in Engineering Systems PDF Author: Subhransu Sekhar Dash
Publisher: Springer
ISBN: 9811078688
Category : Technology & Engineering
Languages : en
Pages : 735

Book Description
The book is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES 2017). The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academia and industry have presented their original work and ideas, information, techniques and applications in the field of communication, computing and power technologies.

Artificial Intelligence and Expert Systems for Engineers

Artificial Intelligence and Expert Systems for Engineers PDF Author: C.S. Krishnamoorthy
Publisher: CRC Press
ISBN: 1351465589
Category : Computers
Languages : en
Pages : 219

Book Description
This book provides a comprehensive presentation of artificial intelligence (AI) methodologies and tools valuable for solving a wide spectrum of engineering problems. What's more, it offers these AI tools on an accompanying disk with easy-to-use software. Artificial Intelligence and Expert Systems for Engineers details the AI-based methodologies known as: Knowledge-Based Expert Systems (KBES); Design Synthesis; Design Critiquing; and Case-Based Reasoning. KBES are the most popular AI-based tools and have been successfully applied to planning, diagnosis, classification, monitoring, and design problems. Case studies are provided with problems in engineering design for better understanding of the problem-solving models using the four methodologies in an integrated software environment. Throughout the book, examples are given so that students and engineers can acquire skills in the use of AI-based methodologies for application to practical problems ranging from diagnosis to planning, design, and construction and manufacturing in various disciplines of engineering. Artificial Intelligence and Expert Systems for Engineers is a must-have reference for students, teachers, research scholars, and professionals working in the area of civil engineering design in particular and engineering design in general.

Intelligent Systems for Engineering

Intelligent Systems for Engineering PDF Author: Ram D. Sriram
Publisher: Springer Science & Business Media
ISBN: 1447106318
Category : Technology & Engineering
Languages : en
Pages : 843

Book Description
When men of knowledge impart this knowledge, I do not mean they will convince your reason. I mean they will awaken in you the faith that it is so. - Sri Krishna, Bhagavadgita BACKGROUND The use of computers has led to significant productivity increases in the en gineering industry. Most ofthe computer-aided engineering applications were . restricted to algorithmic computations, such as finite element programs and circuit analysis programs. However, a number ofproblems encountered in en gineering are not amenable to purely algorithmic solutions. These problems are often ill-structured; the term ill-structured problems is used here to de note problems that do not have a clearly defined algorithmic solution. An experienced engineer deals with these ill-structured problems using his/her judgment and experience. The knowledge-based systems (KBS) technology, which emerged out of research in artificial intelligence (AI), offers a method ologyto solve these ill-structuredengineering problems. The emergenceofthe KBS technology can be viewed as the knowledge revolution: other important events that led to increased productivity are the industrial revolution (17th century); the invention of the transistor and associated developments (first half of the 20th century); and the world-wide web (towards the end of the 20th century). Kurzweil, in a lecture at M. LT on December 3, 1987, linked the progress of automation to two industrial revolutions: the first industrial PREFACE xxxii revolution leveraged our physical capabilities, whereas the second industrial revolution - the knowledge revolution - is expected leverage oUr mental ca pabilities.

Building Intelligent Systems

Building Intelligent Systems PDF Author: Geoff Hulten
Publisher: Apress
ISBN: 1484234324
Category : Computers
Languages : en
Pages : 346

Book Description
Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems. Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You’ll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success Design an intelligent user experience: Produce data to help make the Intelligent System better over time Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice Create intelligence: Use different approaches, including machine learning Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want Who This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems