The Sciences Of The Artificial Reissue Of The Third Edition With A New Introduction By John Laird

Herbert Simon's classic work on artificial intelligence in the expanded and updated third edition from 1996, with a new introduction by John E. Laird. Herbert Simon's classic and influential The Sciences of the Artificial declares definitively that there can be a science not only of natural phenomena but also of what is artificial. Exploring the commonalities of artificial systems, including economic systems, the business firm, artificial intelligence, complex engineering projects, and social plans, Simon argues that designed systems are a valid field of study, and he proposes a science of design. For this third edition, originally published in 1996, Simon added new material that takes into account advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. Simon won the Nobel Prize for Economics in 1978 for his research into the decision-making process within economic organizations and the Turing Award (considered by some the computer science equivalent to the Nobel) with Allen Newell in 1975 for contributions to artificial intelligence, the psychology of human cognition, and list processing. The Sciences of the Artificial distills the essence of Simon's thought accessibly and coherently. This reissue of the third edition makes a pioneering work available to a new audience.

Herbert Simon's classic work on artificial intelligence in the expanded and updated third edition from 1996, with a new introduction by John E. Laird. Herbert Simon's classic and influential The Sciences of the Artificial declares definitively that there can be a science not only of natural phenomena but also of what is artificial. Exploring the commonalities of artificial systems, including economic systems, the business firm, artificial intelligence, complex engineering projects, and social plans, Simon argues that designed systems are a valid field of study, and he proposes a science of design. For this third edition, originally published in 1996, Simon added new material that takes into account advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. Simon won the Nobel Prize for Economics in 1978 for his research into the decision-making process within economic organizations and the Turing Award (considered by some the computer science equivalent to the Nobel) with Allen Newell in 1975 for contributions to artificial intelligence, the psychology of human cognition, and list processing. The Sciences of the Artificial distills the essence of Simon's thought accessibly and coherently. This reissue of the third edition makes a pioneering work available to a new audience.

The development of lawful systems is vital in today’s world. Legal disputes and the advent of regulations pose challenges for developers. At the same time, the application of systems based on artificial intelligence (AI) has gained importance. AI-based systems represent new possibilities in areas such as everyday life and learning situations. However, these systems often lead to legal issues and burden developers with additional development challenges. Designing lawful but equally user-friendly AI-based systems requires consideration of legal requirements to avoid privacy concerns and violations. This dissertation adopts a design science research approach to develop legal design patterns that codify proven legal design knowledge. The dissertation demonstrates how the developed design patterns can be used by developers for the design of lawful AI-based systems, and at the same time support legal experts in making legal judgments. As such, it provides a foundation for codifying legal design knowledge.

This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), which is the integration of geospatial studies and AI machine (deep) learning and knowledge graph technologies. It explains key fundamental concepts, methods, models, and technologies of GeoAI, and discusses the recent advances, research tools, and applications that range from environmental observation and social sensing to natural disaster responses. As the first single volume on this fast-emerging domain, Handbook of Geospatial Artificial Intelligence is an excellent resource for educators, students, researchers, and practitioners utilizing GeoAI in fields such as information science, environment and natural resources, geosciences, and geography. Features Provides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectives Covers a wide range of GeoAI applications and case studies in practice Offers supplementary materials such as data, programming code, tools, and case studies Discusses the recent developments of GeoAI methods and tools Includes contributions written by top experts in cutting-edge GeoAI topics This book is intended for upper-level undergraduate and graduate students from different disciplines and those taking GIS courses in geography or computer sciences as well as software engineers, geospatial industry engineers, GIS professionals in non-governmental organizations, and federal/state agencies who use GIS and want to learn more about GeoAI advances and applications.

This book provides insights into the 5th Edition of the Proceedings of the Conference on Computer Science, Electronics, and Industrial Engineering (CSEI 2022) held in Ambato, Ecuador. This event brings together researchers, students, and professionals from the industrial and academic sectors, seeking to create and strengthen links between issues of joint interest, thus promoting technology and innovation nationwide. The topics of knowledge covered by the event are smart trends for industrial applications, the Internet of things (IoT), control and automation engineering, computer science, and health informatics. The book is helpful for active researchers and practitioners in the field.

ARTIFICIAL INTELLIGENCE IN PERFORMANCE-DRIVEN DESIGN A definitive, interdisciplinary reference to using artificial intelligence technology and data-driven methodologies for sustainable design Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools explores the application of artificial intelligence (AI), specifically machine learning (ML), for performance modeling within the built environment. This work develops the theoretical foundations and methodological frameworks for utilizing AI/ML, with an emphasis on multi-scale modeling encompassing energy flows, environmental quality, and human systems. The book examines relevant practices, case studies, and computational tools that harness AI’s capabilities in modeling frameworks, enhancing the efficiency, accuracy, and integration of physics-based simulation, optimization, and automation processes. Furthermore, it highlights the integration of intelligent systems and digital twins throughout the lifecycle of the built environment, to enhance our understanding and management of these complex environments. This book also: Incorporates emerging technologies into practical ideas to improve performance analysis and sustainable design Presents data-driven methodologies and technologies that integrate into modeling and design platforms Shares valuable insights and tools for developing decarbonization pathways in urban buildings Includes contributions from expert researchers and educators across a range of related fields Artificial Intelligence in Performance-Driven Design is ideal for architects, engineers, planners, and researchers involved in sustainable design and the built environment. It’s also of interest to students of architecture, building science and technology, urban design and planning, environmental engineering, and computer science and engineering.

Strategic innovation dynamically brings about strategic positioning through new products, services and business models, and is a dynamic view of strategy that enables a corporation to maintain its competitive advantage and establish sustainable growth. For these reasons, corporations have to be innovators that can reinforce their existing positions through incremental innovation, while at the same time constantly renewing or destroying existing business through radical innovation. This book presents a holistic theoretical model, The Strategic Innovation System, as a system of capabilities for companies to achieve strategic innovation. As a subsystem of the Strategic Innovation System, this book presents the concept of the “Capabilities Building Map”, which has characteristics of four different capabilities that correspond to the elements of speed of changes and uncertainty in the environment faced by companies. It explores how companies can change and even evolve their capabilities to achieve strategic innovation, using the latest findings of the systems-view, the process-view, and dynamic capabilities-view. The author evaluates management systems that achieve sustainable strategic innovation by utilizing knowledge assets inside and outside of organizations, including those of leaders, rather than simply relying on leaders with strong will. This book will primarily appeal to academics, researchers, and graduate students interested in innovation and technology management, digital transformation as well as strategic management and strategy planning and a broader business audience.