The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes:- the first volume brings together twenty-three chapters dealing with the foundations of knowledge representatio...

The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes:- the first volume brings together twenty-three chapters dealing with the foundations of knowledge representatio...

The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes:- the first volume brings together twenty-three chapters dealing with the foundations of knowledge representatio...

This book provides an overview of the main methods and results in the formal study of the human decision-making process, as defined in a relatively wide sense. A key aim of the approach contained here is to try to break down barriers between various disciplines encompassed by this field, including psychology, economics and computer science. All these approaches have contributed to progress in this very important and much-studied topic in the past, but none have proved sufficient so far to ...

Analogical reasoning is known as a powerful mode for drawing plausible conclusions and solving problems. It has been the topic of a huge number of works by philosophers, anthropologists, linguists, psychologists, and computer scientists. As such, it has been early studied in artificial intelligence, with a particular renewal of interest in the last decade.The present volume provides a structured view of current research trends on computational approaches to analogical reasoning. It...

Human language seems to have arisen roughly within the last 50-100,000 years. In evolutionary terms, this is the mere blink of an eye. If this is correct, then much of what we consider distinctive to language must in fact involve operations available in pre-linguistic cognitive domains. In this book Norbert Hornstein, one of the most influential linguists working on syntax, discusses a topical set of issues in syntactic theory, including a number of original proposals at the cutting edge o...

This book commemorates the 65th birthday of Dr. Boris Kovalerchuk, and reflects many of the research areas covered by his work. It focuses on data processing under uncertainty, especially fuzzy data processing, when uncertainty comes from the imprecision of expert opinions. The book includes 17 authoritative contributions by leading experts.

CAUSAL INFERENCE IN STATISTICSA PrimerCausality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can...

This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. The problems considered are linked to applications aiming at facilitating information access:information extraction and retrieval;text classification and clustering;opinion mining;comprehension aids (automatic summarization, machine translation, visualization).In order to g...

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 ...

Jung's Personality Theory Quantified fills an urgent need for professionals using the Myers-Briggs Type Indicator® (MBTI) to map it on to the cognitive modes of Jung’s personality theory, avoiding potential logical errors in the traditional “type dynamics” method. It furthers Jung’s original concepts while placing them on a solid axiomatic basis not possessed by other personality theories. Bringing these quantitative findings to the millions of MBTI users – managers, consultants, counsello...

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout.Features include: