This book provides a comprehensive, up-to-date, and rigorously detailed introduction to Non-Axiomatic Logic (NAL), a groundbreaking framework for adaptive systems operating under conditions of insufficient knowledge and resources. Designed according to the principles of human cognition, NAL serves as a cornerstone for advancing general-purpose Artificial Intelligence while addressing many topics in logic, psychology, linguistics, philosophy, and computer science.Now fully expanded ...

This book addresses a number of questions from the perspective of complex systems: How can we quantitatively understand the life phenomena? How can we model life systems as complex bio-molecular networks? Are there any methods to clarify the relationships among the structures, dynamics and functions of bio-molecular networks? How can we statistically analyse large-scale bio-molecular networks?Focusing on the modeling and analysis of bio-molecular networks, the book presents various...

This book focuses on the control of fractal behaviors in nonlinear dynamics systems, addressing both the principles and purposes of control. For fractals in different systems, it presents revealing studies on the theory and applications of control, reflecting a spectrum of different control methods used with engineering technology. As such, it will benefit researchers, engineers, and graduate students in fields of fractals, chaos, engineering, etc.

This book characterizes the major pollution patterns of emerging contaminants, such as sources, emission effluents, temporal and spatial distributions, multi-media transportation and transformation processes, exposure pathways to ecosystems and humans, and ecological risks. Based on this, it establishes an urbanizing region management concept and highlights how urbanization and its regional ecology have evolved into a more integrated vision. It also decouples the relations between urbaniza...

A trenchant defense of hierarchy in different spheres of our lives, from the personal to the politicalAll complex and large-scale societies are organized along certain hierarchies, but the concept of hierarchy has become almost taboo in the modern world. Just Hierarchy contends that this stigma is a mistake. In fact, as Daniel Bell and Wang Pei show, it is neither possible nor advisable to do away with social hierarchies. Drawing their arguments from Chine...

This book constitutes the refereed proceedings of the 9th International Conference on Artificial General Intelligence, AGI 2016, held in New York City, NY, USA, in July 2016 as part of HLAI 2016, the Joint Multi-Conference on Human-Level Artificial Intelligence 2016.The 24 full papers, 2 short papers, and 10 poster papers presented were carefully reviewed and selected from 67 submissions. AGI research differs from the ordinary AI research by stressing on the versatility and wholene...

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics ...

The field's leading text, now completely updated.Modeling dynamical systems — theory, methodology, and applications.Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-f...

This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficult...

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provid...

This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting,” how to exploit them in m...

Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one anotherThis book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise compu...