Bøker i Frontiers in Artificial Intelligence and Applications-serien

This volume presents research from the interdisciplanary field of norms, logic and information systems, a cross-pollinations between traditional deontic logic and computer science.

This work contains a selection of contributions regarding intelligent systems by experts in diverse fields. Topics discussed are: applications of intelligent systems in modelling and prediction of environmental changes; and neural networks for signal processing.

This volume provides an in-depth analysis of knowledge modelling technology, illustrating the main tenets of this paradigm, surveying the state of the art and then presenting in detail the application of this technology to parametric design problems.

Provides a detailed overview of Inductive Logic Programming, as well as a collection of technical contributions to it. This overview is based on the ESPRIT basic research project no 6020 on Inductive Logic Programming. It is useful for students, researchers and practitioners of artificial intelligence and computer science.

If a technique represents a genuine advance in software engineering, then it has commercial advantage. This trend is more evident in the application of genetic algorithms (GAs). This book attempts to emphasise the diversity of the GA approach, by presenting descriptions of GAs used for real-world optimization and for complex modelling problems.

Addresses several functional areas such as: planning, scheduling, monitoring, control, fault classification and diagnosis, training, and help desks. This book is of interest to researchers and professionals in telecommunication, AI experts, and graduate students.

Reflects on the discussion on using chaos theory for the study of society. This book explores the interface between chaos theory and the social sciences. A broad variety of fields (including Sociology, Anthropology, Economics, Political Science, Management, Philosophy and Cognitive Sciences) are represented.

Current approaches to the development of legal knowledge-based systems (LKBS), such as the use of rule-based systems, case-based systems or logics, have obtained limited theoretical and practical results. This overview of the field describes present approaches and analyzes their problems.

This book is intended to provide a treatment of the theory and applications of Stochastic Neural Networks, that is networks able to learn random processes from experience, on the basis of recent developments on this subject.

Bringing artificial intelligence planning and scheduling applications into the real world is a hard task that is receiving more attention every day by researchers and practitioners from many fields. In many cases, it requires the integration of several underlying techniques like planning, scheduling, constraint satisfaction, mixed-initiative planning and scheduling, temporal reasoning, knowledge representation, formal models and languages, and technological issues. Most papers included in this book are clear examples on how to integrate several of these techniques. Furthermore, the book also covers many interesting approaches in application areas ranging from industrial job shop to electronic tourism, environmental problems, virtual teaching or space missions. This book also provides powerful techniques that allow to build fully deployable applications to solve real problems and an updated review of many of the most interesting areas of application of these technologies, showing how powerful these technologies are to overcome the expresiveness and efficiency problems of real world problems.