Knowledge Systems And Prolog

Not long ago" Dennis Merritt wrote one of the best books that I know of about implementing expert systems in Prolog, and I was very glad he published it in our series. The only problem is there are still some unfortunate people around who do not know Prolog and are not sufficiently prepared either to read Merritt's book, or to use this extremely productive language, be it for knowledge-based work or even for everyday programming. Possibly this last statement may surprise you if you were under the impression that Prolog was an "artificial intelligence language" with very limited application potential. Please believe this editor's statement that quite the opposite is true: for at least four years, I have been using Prolog for every programming task in which I am given the option of choosing the language. Therefore, I 'am indeed happy that Dennis Merritt has written another good book on my language of choice, and that it meets the high standard he set with his prior book, Building Expert Systems in Prolog. All that remains for me to do is to wish you success and enjoyment when taking off on your Adventure in Prolog.

The machine learning capabilities of today's AI are extremely exciting, but they are only one part of the architecture of today's systems. For example, self-driving car technology uses machine learning to interpret the visual field around a car, but it's good old fashioned rule-based AI that contains the plans on what to do with that information.Similarly, the phenomenal program that plays Go at a master level uses machine learning to evaluate board positions (very difficult for a machine to do) but uses conventional AI for deciding what to do with that information.Written a number of years ago, Building Expert Systems in Prolog is still a classic text on knowledge engineering. The name might be a bit misleading, as it's not so much about building expert systems, but rather on building the knowledge representation and reasoning engine tools used for various types of expert system applications. (Including, of course, examples of each kind of system.)As such, it provides details and working code for identification systems, systems that need to cope with uncertainty, forward-chaining planning and configuration systems, frames for representing complex layers of information, and ideas for prototyping/implementing any way of representing knowledge and algorithms for reasoning over that knowledge.The text is a bit more general than just a Prolog text. Yes, all the code for implementing these systems is written in Prolog, but Prolog is more than just an implementation language. Because it is logic programming, a Prolog program is really a logical specification of an application. Yes it runs, but it can also be used for rapid prototyping, and the Prolog code itself can be used to precisely specify how to implement the system in any other language.In other words, the architectures of these systems will be the same, no matter what language they are implemented in, and the use of Prolog for rapid prototyping is covered in the book as well.

If one were forced to use a single key word to describe the decade of the 1980's, a very prominent one would be "technology. " Leading the forefront of tech nology advancement were breakthroughs in electronics. Devices that were uncommon or unknown in 1980 became commonplace, and almost indispens able, by 1989. This trend has continued into the 1990's and it does not seem to be abating in any way. Microwave ovens, video recorders, telephone answer ing machines, compact disc players, computers, and a host of smaller or less sophisticated devices now appear in most households. The development of small and inexpensive computers, i. e. , personal computers, has placed computing resources within reach of many more people. In addition, many traditional, and largely mechanical devices, have been enhanced by electronics. For example, specialized microprocessors are combined with arrays of electronic sensors to control and monitor sophisticated engineering components in most new auto mobiles. In this and many other ways, we are touched by the new electronics in almost every aspect of our daily lives. Initially, personal computers were little more than toys. They contained only a small fraction of the computing power of their immediate ancestors, the mini computers and mainframe computers. However, rapid improvements in integ rated circuit design and chip manufacture produced regular reductions in size and cost of computer components. During the same time, processor speed and sophistication increased.

Although many texts exist offering an introduction to artificial intelligence (AI), this book is unique in that it places an emphasis on knowledge representation (KR) concepts. It includes small-scale implementations in PROLOG to illustrate the major KR paradigms and their developments.****back cover copy:**Knowledge representation is at the heart of the artificial intelligence enterprise: anyone writing a program which seeks to work by encoding and manipulating knowledge needs to pay attention to the scheme whereby he will represent the knowledge, and to be aware of the consequences of the choices made.****The book's distinctive approach introduces the topic of AI through a study of knowledge representation issues. It assumes a basic knowledge of computing and a familiarity with the principles of elementary formal logic would be advantageous.****Knowledge Representation: An Approach to Artificial Intelligence develops from an introductory consideration of AI, knowledge representation and logic, through search technique to the three central knowledge paradigms: production rules, structured objects, and predicate calculus. The final section of the book illustrates the application of these knowledge representation paradigms through the Prolog Programming language and with an examination of diverse expert systems applications. The book concludes with a look at some advanced issues in knowledge representation.****This text provides an introduction to AI through a study of knowledge representation and each chapter contains exercises for students. Experienced computer scientists and students alike, seeking an introduction to AI and knowledge representations will find this an invaluable text.

Designed for undergraduate courses on Expert Systems, PROLOG or introductory Artificial Intelligence, this informally-styled text assumes no background in PROLOG or Logic Programming, but combines an introduction to PROLOG with a mastery of its application to expert systems programming.

Provide research communities in information modelling and knowledge bases with scientific results and experiences achieved by using innovative methodologies in computer science and other disciplines related to linguistics, philosophy, and psychology.