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Approaches the subject by applying the format used in successful language courses. Offers a comprehensive exhibition of Prolog programming techniques in four stages--declarative, procedural, advanced and meta-programming. Presents simple and efficient implementation of logical negation and quantified goals which are necessary in expert systems. The dynamics of these new features are shown in the construction of a multilingual expert system shell that supports negative and quantified queries as well as subtypes. The easy-to-follow tutorial style and numerous fully-solved exercises facilitate understanding. Comes with 3.5 inch disk containing all programs in the book.
Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed. Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prolog terms and rules (and Prolog facts as special cases); unification; the and-or computation tree induced by a Prolog program and a query; the depth-first, left-to-right traversal of that tree by the standard Prolog interpreter; and built-in predicates such as unification and equality. Subsequent chapters deal with search and representation of graphs in Prolog; backward-chaining methods; truth maintenance systems; and constraint satisfaction. Reasoning with uncertainty, planning and temporal reasoning, and machine learning are also tackled. The book concludes with an assessment of natural language processing and some of the linguistic notions that are easily encoded in Prolog. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.
The computer programming language Prolog is quickly gaining popularity throughout the world. Since Its beginnings around 1970. Prolog has been chosen by many programmers for applications of symbolic computation. including: D relational databases D mathematical logic D abstract problem solving D understanding natural language D architectural design D symbolic equation solving D biochemical structure analysis D many areas of artificial Intelligence Until now. there has been no textbook with the aim of teaching Prolog as a practical programming language. It Is perhaps a tribute to Prolog that so many people have been motivated to learn It by referring to the necessarily concise reference manuals. a few published papers. and by the orally transmitted 'folklore' of the modern computing community. However. as Prolog is beginning to be Introduced to large numbers of undergraduate and postgraduate students. many of our colleagues have expressed a great need for a tutorial guide to learning Prolog. We hope this little book will go some way towards meeting this need. Many newcomers to Prolog find that the task of writing a Prolog program Is not like specifying an algorithm in the same way as In a conventional programming language. Instead. the Prolog programmer asks more what formal relationships and objects occur In his problem.
Written for those who wish to learn Prolog as a powerful software development tool, but do not necessarily have any background in logic or AI. Includes a full glossary of the technical terms and self-assessment exercises.
This new edition of The Art of Prolog contains a number of important changes. Most background sections at the end of each chapter have been updated to take account of important recent research results, the references have been greatly expanded, and more advanced exercises have been added which have been used successfully in teaching the course. Part II, The Prolog Language, has been modified to be compatible with the new Prolog standard, and the chapter on program development has been significantly altered: the predicates defined have been moved to more appropriate chapters, the section on efficiency has been moved to the considerably expanded chapter on cuts and negation, and a new section has been added on stepwise enhancement—a systematic way of constructing Prolog programs developed by Leon Sterling. All but one of the chapters in Part III, Advanced Prolog Programming Techniques, have been substantially changed, with some major rearrangements. A new chapter on interpreters describes a rule language and interpreter for expert systems, which better illustrates how Prolog should be used to construct expert systems. The chapter on program transformation is completely new and the chapter on logic grammars adds new material for recognizing simple languages, showing how grammars apply to more computer science examples.
Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.