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Intelligent knowledge-based systems, An introduction
International Journal of Industrial Ergonomics, 5 (1990) 185-189
185
Elsevier
BOOK REVIEWS
Intelligent Knowledge-Based Systems, An Introduction, edited by Tim O'Shea, John Self, Glen
Thomas, Harper and Row, London, 1987, ISBN 0-06-318366-8, 227 pages. As the title indicates, this book is just an introduction to intelligent knowledge based systems and I would recommend it only to those who would like a glimpse of the field of artificial intelligence. This book is essentially made up of a collection of written versions of videotaped lectures on Intelligent Knowledge Based Systems (IKBS) presented as a part of the Alvey Program in the United Kingdom. Each chapter in the book is a lecture delivered by a different person, the topics include artificial intelligence languages, an expert system for medical diagnosis, dealing with uncertainty, an introduction to production systems, logic programming in artificial intelligence and software engineering, expert systems--some user experience, artificial intelligence: next generation solutions, image understanding, machine learning, natural language processing, and proving the correctness of digital hardware designs. A major complaint that I had while reading this book was the lack of blending of the different topics. This may have been partly due to the way the book was put together. Different people have different styles of presentation and it is difficult to blend all these styles together. However, this reviewer feels that if some more thought had been given to organization, it would have greatly improved the book's impact. For instance, if the first chapter were to present a framework of the organization of the book and a summary of what followed in the remaining chapters it would have considerably enhanced the books readability and understanding. The reviewer feels that these two criteria are important in an introductory book. The following sections in this review provide a brief summary of the different chapters, with comments interjected where appropriate. In the first chapter of the book, "IKBS--Setting the Scene", Jim Howe introduces a variety of topics, these include machine transalation, language understanding, speech understanding, image
understanding and expert systems. He provides a brief status report of these areas and provides potential areas of application. For instance, he points out that the failure of early machine translation programs were due to the failure of linguistic theory not technology, and discusses the problems of mapping from one representation to another for machine understanding. He explains that in speech understanding, the fundamental problem is to break a continuous speech wave form into segments. He suggests that the difficulties in image understanding arise owing to the ambiguities that result from collapsing three dimensions into two. He presents examples of how an expert system automates the thinking process and presents potential uses of expert systems as intelligent front ends and for computer aided instructions. He concludes his discussion with the advantages offered by A.I. programming environments. The second chapter is a basic discussion of "Artificial Intelligence Languages", such as LISP, POP-11 and PROLOG, by Aaron Sloman. In the third chapter "An Expert System for Medical Diagnosis" Alan Bundy basically provides an overview of MYCIN, using examples from the MYCIN rule base and the use of certainty factors. In the fourth chapter "Dealing with Uncertainty" John Fox provides an overview of where uncertainty could occur in knowledge based systems specifically in rule based systems, i.e., in the premise, conclusions and the heuristic itself. He, however, ignores the subjective uncertainty in heuristics and does not mention the theory of fuzzy sets. The fifth chapter, " A n Introduction to Production Systems" is well written. Here, Richard M. Young provides an explanation of the recognizeact cycle in production systems and the elements of production systems, i.e., facts, working memory and the rule base. He explains consequent and condition driven inference strategies and discusses conflict resolution. He also provides clarifying examples using working expert systems, such as MYCIN, RITA and OPS.
186 In the sixth chapter, "Logic Programming in Artificial Intelligence and Software Engineering", Robert Kowalski discusses the role of logic programming in A.I. and software engineering. He suggests that logic programming allows knowledge to be represented explicitly and hence enhances understanding. The latter property enables rapid prototyping in the early stages of software development; this is because system specifications and the program can be written in the same language. The seventh chapter, "Expert Systems--Some User Experience" is just a very general overview of experiences at UNILEVER in knowledge acquisition, and building small expert systems. In the eight chapter Arnold Kraft in "Artificial Intelligence: The Next Generation Solutions", discusses the applications of A.I. at Digital Equipment Corporation. He presents the well publicized A.I. applications at Digital, namely, XCON and XSEL and some experiences learnt from them. In the ninth chapter, "Image Understanding", John Frisby reviews difficulties with achieving a flexible general purpose vision system. He discusses the need for multiple levels of representation and levels of analysis to make the scene more explicit. The representations discussed include primal sketch, 2 and a 1/2 D sketch and 3D object model representations. In the tenth chapter, "Machine Learning", Tim O'Shea discusses the different types of learning and discusses some of the difficulties in machine learning. The eleventh chapter is on "Natural Language Processing". Here, Karen Sparck Jones provides an overview of the issues in natural language systems, and an example of the natural language system LUNAR. She also discusses the problems with ambiguity and the use of information on syntax, semantics and pragmatics to reduce the problem. She concludes by providing several examples of natural language systems that have been built. The twelfth chapter, "Proving the Correctness of Digital Hardware Designs", by Harry Barrow discusses using the structure and behaviour of digital systems to make inferences. This reviewer feels that the material in this chapter is a little too advanced for an introductory book. S. A L E X A N D E R
Applied Artificial Intelligence in Japan, by Bruce Rubinger, Hemisphere Publishing Co., New York, 1988, ISBN 0-89116-744-7, 256 pages.
The book evolved from the analysis of technical trends in Japan and the factors contributing to effective management of technology that has been performed by the author. As Director of Studies of the Global Competitiveness Council, a hightechnology research company, the author has assessed emerging technologies research and development productivity in Japan on behalf of numerous government agencies and private sector firms. This intends to overcome the barriers between the U.S. and Japanese artificial intelligence (AI) communities. It utilizes Japanese-language materials and provide timely, comprehensive information on the development of artificial intelligence in Japan. It is the author's hope that the book will lead to positive interaction that balances competition with cooperation. The book is designed for readers in manufacturing companies involved in the production of automobiles, computers, factory automation products, optics, software, steel, and telecommunications; government agencies; public utilities; and service industries such as banking. The book emphasizes that effective decision making requires timely, in-depth information on AI products, market trends, technical activities, and applications. If U.S. industry is to prosper in the present global era, it must respect the technical activity taking place abroad, value external learning as highly as internal research and development, and create mechanisms to assimilate this knowledge. This book is a useful reading material for users of AI technologies, consultants, and academics interested in AI opportunities.
ANDREW KUSIAK
University of Iowa Iowa City, 1A 52242, IZS.A.
185
Elsevier
BOOK REVIEWS
Intelligent Knowledge-Based Systems, An Introduction, edited by Tim O'Shea, John Self, Glen
Thomas, Harper and Row, London, 1987, ISBN 0-06-318366-8, 227 pages. As the title indicates, this book is just an introduction to intelligent knowledge based systems and I would recommend it only to those who would like a glimpse of the field of artificial intelligence. This book is essentially made up of a collection of written versions of videotaped lectures on Intelligent Knowledge Based Systems (IKBS) presented as a part of the Alvey Program in the United Kingdom. Each chapter in the book is a lecture delivered by a different person, the topics include artificial intelligence languages, an expert system for medical diagnosis, dealing with uncertainty, an introduction to production systems, logic programming in artificial intelligence and software engineering, expert systems--some user experience, artificial intelligence: next generation solutions, image understanding, machine learning, natural language processing, and proving the correctness of digital hardware designs. A major complaint that I had while reading this book was the lack of blending of the different topics. This may have been partly due to the way the book was put together. Different people have different styles of presentation and it is difficult to blend all these styles together. However, this reviewer feels that if some more thought had been given to organization, it would have greatly improved the book's impact. For instance, if the first chapter were to present a framework of the organization of the book and a summary of what followed in the remaining chapters it would have considerably enhanced the books readability and understanding. The reviewer feels that these two criteria are important in an introductory book. The following sections in this review provide a brief summary of the different chapters, with comments interjected where appropriate. In the first chapter of the book, "IKBS--Setting the Scene", Jim Howe introduces a variety of topics, these include machine transalation, language understanding, speech understanding, image
understanding and expert systems. He provides a brief status report of these areas and provides potential areas of application. For instance, he points out that the failure of early machine translation programs were due to the failure of linguistic theory not technology, and discusses the problems of mapping from one representation to another for machine understanding. He explains that in speech understanding, the fundamental problem is to break a continuous speech wave form into segments. He suggests that the difficulties in image understanding arise owing to the ambiguities that result from collapsing three dimensions into two. He presents examples of how an expert system automates the thinking process and presents potential uses of expert systems as intelligent front ends and for computer aided instructions. He concludes his discussion with the advantages offered by A.I. programming environments. The second chapter is a basic discussion of "Artificial Intelligence Languages", such as LISP, POP-11 and PROLOG, by Aaron Sloman. In the third chapter "An Expert System for Medical Diagnosis" Alan Bundy basically provides an overview of MYCIN, using examples from the MYCIN rule base and the use of certainty factors. In the fourth chapter "Dealing with Uncertainty" John Fox provides an overview of where uncertainty could occur in knowledge based systems specifically in rule based systems, i.e., in the premise, conclusions and the heuristic itself. He, however, ignores the subjective uncertainty in heuristics and does not mention the theory of fuzzy sets. The fifth chapter, " A n Introduction to Production Systems" is well written. Here, Richard M. Young provides an explanation of the recognizeact cycle in production systems and the elements of production systems, i.e., facts, working memory and the rule base. He explains consequent and condition driven inference strategies and discusses conflict resolution. He also provides clarifying examples using working expert systems, such as MYCIN, RITA and OPS.
186 In the sixth chapter, "Logic Programming in Artificial Intelligence and Software Engineering", Robert Kowalski discusses the role of logic programming in A.I. and software engineering. He suggests that logic programming allows knowledge to be represented explicitly and hence enhances understanding. The latter property enables rapid prototyping in the early stages of software development; this is because system specifications and the program can be written in the same language. The seventh chapter, "Expert Systems--Some User Experience" is just a very general overview of experiences at UNILEVER in knowledge acquisition, and building small expert systems. In the eight chapter Arnold Kraft in "Artificial Intelligence: The Next Generation Solutions", discusses the applications of A.I. at Digital Equipment Corporation. He presents the well publicized A.I. applications at Digital, namely, XCON and XSEL and some experiences learnt from them. In the ninth chapter, "Image Understanding", John Frisby reviews difficulties with achieving a flexible general purpose vision system. He discusses the need for multiple levels of representation and levels of analysis to make the scene more explicit. The representations discussed include primal sketch, 2 and a 1/2 D sketch and 3D object model representations. In the tenth chapter, "Machine Learning", Tim O'Shea discusses the different types of learning and discusses some of the difficulties in machine learning. The eleventh chapter is on "Natural Language Processing". Here, Karen Sparck Jones provides an overview of the issues in natural language systems, and an example of the natural language system LUNAR. She also discusses the problems with ambiguity and the use of information on syntax, semantics and pragmatics to reduce the problem. She concludes by providing several examples of natural language systems that have been built. The twelfth chapter, "Proving the Correctness of Digital Hardware Designs", by Harry Barrow discusses using the structure and behaviour of digital systems to make inferences. This reviewer feels that the material in this chapter is a little too advanced for an introductory book. S. A L E X A N D E R
Applied Artificial Intelligence in Japan, by Bruce Rubinger, Hemisphere Publishing Co., New York, 1988, ISBN 0-89116-744-7, 256 pages.
The book evolved from the analysis of technical trends in Japan and the factors contributing to effective management of technology that has been performed by the author. As Director of Studies of the Global Competitiveness Council, a hightechnology research company, the author has assessed emerging technologies research and development productivity in Japan on behalf of numerous government agencies and private sector firms. This intends to overcome the barriers between the U.S. and Japanese artificial intelligence (AI) communities. It utilizes Japanese-language materials and provide timely, comprehensive information on the development of artificial intelligence in Japan. It is the author's hope that the book will lead to positive interaction that balances competition with cooperation. The book is designed for readers in manufacturing companies involved in the production of automobiles, computers, factory automation products, optics, software, steel, and telecommunications; government agencies; public utilities; and service industries such as banking. The book emphasizes that effective decision making requires timely, in-depth information on AI products, market trends, technical activities, and applications. If U.S. industry is to prosper in the present global era, it must respect the technical activity taking place abroad, value external learning as highly as internal research and development, and create mechanisms to assimilate this knowledge. This book is a useful reading material for users of AI technologies, consultants, and academics interested in AI opportunities.
ANDREW KUSIAK
University of Iowa Iowa City, 1A 52242, IZS.A.