Dov M. Gabbay

Artur S. d'Avila Garcez

Krysia Broda

Augustus de Morgan Professor of Logic Dov M Gabbay

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.

Foundations and Applications

Neural-Symbolic Learning Systems

Since its conception nearly 20 years ago, logic programming has been developed to the point where it now plays an important role in areas such as database theory, artificial intelligence and software engineering. There are, however, still many outstanding research issues which need to be addressed, and the UK branch of the Association for Logic Programming was set up to provide a forum where the flourishing research community could discuss important issues which were often by- passed at the larger international conferences. This volume contains the invited papers, refereed papers and tutorials presented at the 4th ALPUK Conference, which aimed to broaden the frontiers of logic programming by encouraging interaction between it and other related disciplines. The papers cover a variety of technical areas, including concurrent logic languages and their semantics, applications of logic languages to other (non-classical) logical systems, modules, types and error-handling, and the distributed execution of Prolog programs. The wide scope of the papers refelects the breadth of interest in this important area of computer science. ALPUK 92 provides a comprehensive overview of current progress being made in logic programming research. It will be of interest to all workers in the field, especially researchers, postgraduate students, and research and development workers in industry.

Krysia Broda

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