by William F. Clocksin, Christopher S. Mellish (1984)
Since the first edition of this book in 1981, Prolog has continued to attract an unexpectedly great deal of interest in the computer science community and has turned out to be a basis for an important new family of programming languages and systems for Artificial Intelligence. In the preceding three editions, the authors have steadily added new material, improved the presentation, and corrected various minor errors to provide a textbook as well as a reference work for everyone who wants to study and use Prolog as a practical programming language. The authors concentrate on teaching "core" Prolog. All examples conform to this standard and will run on the most widely-used Prolog implementations some of which are listed in the appendices with indications as to how they diverge from the standard.
Timothy J. Brown, Paul W. Mielke
Statistical Mining and Data Visualization in Atmospheric Sciences brings together in one place important contributions and up-to-date research results in this fast moving area. Statistical Mining and Data Visualization in Atmospheric Sciences serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
Ming Li, Akira Maruoka (eds
This book constitutes the refereed proceedings of the 8th International Workshop on Algorithmic Learning Theory, ALT'97, held in Sendai, Japan, in October 1997. The volume presents 26 revised full papers selected from 42 submissions. Also included are three invited papers by leading researchers. Among the topics addressed are PAC learning, learning algorithms, inductive learning, inductive inference, learning from examples, game-theoretical aspects, decision procedures, language learning, neural algorithms, and various other aspects of computational learning theory.
Alan F. Murray
Applications of Neural Networks gives a detailed description of 13 practical applications of neural networks, selected because the tasks performed by the neural networks are real and significant. The contributions are from leading researchers in neural networks and, as a whole, provide a balanced coverage across a range of application areas and algorithms. The book is divided into three sections. Section A is an introduction to neural networks for nonspecialists. Section B looks at examples of applications using `Supervised Training'. Section C presents a number of examples of `Unsupervised Training'. For neural network enthusiasts and interested, open-minded sceptics. The book leads the latter through the fundamentals into a convincing and varied series of neural success stories -- described carefully and honestly without over-claiming. Applications of Neural Networks is essential reading for all researchers and designers who are tasked with using neural networks in real life applications.
Witold Pedrycz
Granular Computing is concerned with constructing and processing carried out at the level of information granules. Using information granules, we comprehend the world and interact with it, no matter which intelligent endeavor this may involve. The landscape of granular computing is immensely rich and involves set theory (interval mathematics), fuzzy sets, rough sets, random sets linked together in a highly synergetic environment. This volume is a first comprehensive treatment of this emerging paradigm and embraces its fundamentals, underlying methodological framework, and a sound algorithmic environment. The panoply of applications covered includes system identification, telecommunications, linguistics and music processing. Written by experts in the field, this volume will appeal to all developing intelligent systems, either working at the methodological level or interested in detailed system realization.