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.
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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.