Artificial intelligence books

E. Rich, Artificial Intelligence McGraw-Hill Book Co., Inc., New York, 1983. 

The method is different in nature from the techniques discussed elsewhere in this book because, despite the fact that the cells that comprise a CA model evolve, they do not learn. The lack of a learning mechanism places the method at the boundaries of Artificial Intelligence, but the algorithm still has features in common with AI methods and offers an intriguing way to solve scientific problems. 

Computer scientists may use this book to gain a clearer picture of how experimental scientists use Artificial Intelligence tools. Chemists, biochemists, physicists, and others in the experimental sciences who have data to analyze or simulations to run will find tools within these pages that may speed up their work or make it more effective. For both groups, the aim of this book is to encourage a broader application of these methods. 

Kurzweil, Ray, The Age of Intelligent Machines. (Cambridge, Massachusetts MIT Press, 1990). (This book contains information on pattern recognition, the science of art, computer-generated poetry, and artificial intelligence.)... 

Table 6 contains books on artificial intelligence and neural networks as related to chemistry. Also included are books on chemometrics. Table 7 is a compilation of computational chemistry books focused on pertinent areas of physical chemistry crystallography, spectroscopy, and thermodynamics. 

Mulhall, Dou as. Our Molecular Future How Nanotechnology, Robotics, Genetics, and Artificial Intelligence Will Change Our World. Amherst, NY Prometheus Books, 2002. 

The method developed in this book can also provide input parameters (either calculated material properties or a set of simple and unambiguous structural descriptors) into many other types of models. Such models range from phenomenological theories of polymer properties to software tools based on artificial intelligence. Some work stimulated in these directions as a result of the publication of the earlier editions of this book will be discussed in Section 17.G. 

An important long-term goal is to couple the QSPR scheme developed in this book with artificial intelligence tools [11,22], to develop expert systems with combinatorial search and reverse engineering capabilities [23], (See Venkatasubramanian et al [24-26] for an attempt... 

The main thrust of this book is to present examples of how expert systems can solve chemical problems. To make the book more useful to novices in the field of artificial intelligence, we have written a brief introductory chapter explaining expert systems. The glossary at the end of the introduction should be of help to novices and experts alike. We have also included highlights of a panel discussion held at the symposium. The panel was posed the question, Can knowledge bases be made generally available in a useful format Unfortunately, more issues were raised than questions answered. 

The book (25) "Programmable Controllers Theory and Implementation" is a good overview which includes a chapter on "Artificial Intelligence and PLC Systems". More and more devices, such as Foxboro s EXACT system, include "artificial intelligence based" adaptive, self-tuning features. 

R.K. Lindsay, Applications of Artificial Intelligence for Organic Chemistry The DENDRAL Project, McGraw-Hill Book, New York, 1980. 

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