Artificial Intelligence Avron Barr Handbook Volume 1

The Handbook of Artificial Intelligence

What is a "heuristic problem-solving program?" How do computers understand English? What are "semantic nets" or "frames?" Can computer programs outperform human experts? Such questions -- asked by scientists, engineers, students, and hobbyists encountering Artificial Intelligence for the first time -- can now be readily answered by The Handbook of Artificial Intelligence, a work which makes the full scope of important techniques and concepts of AI available for the first time to the rapidly expanding world of computer technologists and users. The scope of this handbook is broad: over 200 short articles covering all of the important ideas, techniques, and systems developed during 25 years of research in the AI field. The articles are written for people with no background in AI. Some articles serve as overviews, discussing the various approaches within a subfield, the issues, and the problems. The handbook is a reference work, a textbook, a guide to programming techniques and to the extensive literature of the field, and a book for intellectual browsing. Jargon has been eliminated in each of the short, penetrating articles, and the hierarchical organization of the book allows readers to choose how deeply they wish to delve into a particular subject. Conceived and produced at Stanford University's Department of Computer Science, with contributions from universities and laboratories across the nation, The Handbook of Artificial Intelligence promises to become the standard reference work in the rapidly growing AI field. - Jacket.

The Handbook of Artificial Intelligence

The Handbook of Artificial Intelligence

The Handbook of Artificial Intelligence, Volume I focuses on the progress in artificial intelligence (AI) and its increasing applications, including parsing, grammars, and search methods. The book first elaborates on AI, AI handbook and literature, problem representation, search methods, and sample search programs. The text then ponders on representation of knowledge, including survey of representation techniques and representation schemes. The manuscript explores understanding natural languages, as well as machine translation, grammars, parsing, test generation, and natural language processing systems. The book also takes a look at understanding spoken language, including systems architecture and the ARPA SUR projects. The text is a valuable source of information for computer science experts and researchers interested in pursuing further research in artificial intelligence.