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 ...

The authors present a systematic development of the concurrent object-oriented agent programming language Guarded Definite Clauses (GDC). In contrast to other languages used in agent programming, like Java, Telescript, and Agent-TCL, this language is derived from the artificial intelligence programming tradition and emphasizes AI applications. The first part of the book is devoted to the principled evolution of the paradigm GDC; during the ...

This textbook covers logical and relational learning in depth, and hence provides an introduction to inductive logic programming (ILP), multirelational data mining (MRDM) and (statistical) relational learning (SRL). These subfields of data mining and machine learning are concerned with the analysis of complex and structured data sets that arise in numerous applications, such as bio- and chemoinformatics, network analysis, Web mining, and natural ...