This book is intended to be a primer for microcomputer users (especially BASIC programmers) interested in learning to program in LISP, one of the most prevalent languages of the Artificial Intelligence (AI) research and programming community. The book assumes the reader is competent in programming, and BASIC is used as a language to highlight the similarities and differences between LISP programming and programming in more conventional languages. The book has an introductory chapter on AI, followed by six more chapters that describe the fundamentals of LISP: the constructs for setting up functions, conditionals, and loops; list processing techniques; recursion; a brief explanation of the use of some advanced LISP functions; and, finally, a chapter on LISP programming in AI. Two appendices include a list of the definition of the standard LISP functions, and a description of the Acornsoft LISP editor.

The book is extremely readable, and some one with access to a LISP interpreter can go through the entire book, doing all the exercises, in less than four weekends at an easy pace. As the book’s own introductory material points out, it is intended to be a primer, and I would recommend no more. A professional seriously in pursuit of AI projects would do well to follow up this book with more advanced texts, both on the theory and programming methodologies of AI. As a starting point though, this book offers a remarkably comfortable introduction to LISP. The readership that will benefit the most from this book would be those well versed in other programming languages, who are looking for a quick tutorial on LISP programming techniques and their usefulness.

The introductory chapter, Introduction to Artificial Intelligence, is the only chapter in the book about which I have misgivings. The concept of AI, as explained here, is highly simplistic, and sometimes misleading (e.g., the sub-section on “Expert Systems and Data Structure” blurs the difference between database and knowledge base). To be fair though, the author does point out that the book is “confined to a few of the simpler AI topics,” and is aimed at giving a “good grounding in an important AI language.”

The next six chapters vindicate that aim, and I found them to be clear, readable and very well organized. In particular, the author has done a very good job of explaining the programming of recursive functions in LISP. This should be appreciated by readers who have not been confronted by the concept before. The exercises in each chapter are very appropriate and instructive, if done. Chapter 7, LISP Programming and AI, ties it all together, using an example of programming in LISP to build a system for decoding encrypted messages. By using a heuristic approach to the decoding process (based on learned frequencies of patterns in the occurrences of the alphabet in normal text, and transposing that on the frequencies of occurrences of the alphabet in the encrypted text for the purpose of extracting the original), the example illustrates extremely well both the nature of uncertainties that lie in problems being addressed by AI systems, and how LISP allows quick programming and testing of such systems. Maintaining LISP code is almost impossible without a syntax-directed editor, and the point is brought home in this book via an appendix that describes the use of one such editor that comes with the Acornsoft LISP package.

Overall, the book definitely scores points for its easy readability, and its brief, to-the-point description and explanation of LISP concepts. It is an ideal beginner’s LISP text for the busy DP professional.