This first volume in the series "Algorithms and Computation in Mathematics", is destined to become the standard reference work in the field. Manuel Bronstein is the number-one expert on this topic and his book is the first to treat the subject both comprehensively and in sufficient detail - incorporating new results along the way. The book addresses mathematicians and computer scientists interested in symbolic computation, developers and programmers of computer algebra systems as well as users of symbolic integration methods. Many algorithms are given in pseudocode ready for immediate implementation, making the book equally suitable as a textbook for lecture courses on symbolic integration.

First edition received rave reviews The second edition offers a new chapter on parallel integration Includes additional exercises

Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. This book provides a comprehensive introduction to the field of neural-symbolic learning systems, and an invaluable overview of the latest research issues in this area. It is divided into three sections, covering the main topics of neural-symbolic integration - theoretical advances in knowledge representation and learning, knowledge extraction from trained neural networks, and inconsistency handling in neural-symbolic systems. Each section provides a balance of theory and practice, giving the results of applications using real-world problems in areas such as DNA sequence analysis, power systems fault diagnosis, and software requirements specifications. Neural-Symbolic Learning Systems will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest to Intelligent Systems practitioners and anyone interested in applications of hybrid artificial intelligence systems.

Using a unique step-by-step,integrated approach, this book organizes the basic concepts of symbolic interactionism in such a way that readers understand them clearly and are able toapply them to their own lives. It emphasizes the active side of human beings-humans as definers and users of the environment, humans as problem solvers and in control of their own actions-and it shows students how society makes us, and how we in turn shape society. Each chapter examines a single concept, but relates that concept to the whole perspective and to other concepts in the perspective. Chapter titles include The Perspective of Social Science, Symbolic Interactionism as a Perspective, The Meaning of the Symbol, The Importance of the Symbol, The Nature of Self, The Human Mind, Taking the Role of the Other, Human Action, Social Interaction, and Society. For individuals interested in the study of social psychology and/or social theory.