In the editor’s words, this catalogue is a collection of “algorithms, data (knowledge) formalisms, architectures, and methodological techniques.” It is an interesting reference work for those working in artificial intelligence. Each of the 256 entries is either an abstract-length reference to other works or a self-contained definition. Many of the classic works of AI are referenced many times by these abstracts, and the editor has done an excellent job of maintaining internal references between topics. The abstracts are numbered consecutively and reference each other using these numbers. The range of material addressed in this text can be illustrated by page 70. On this page a “hook” is defined as “a piece of code or data-structure in an implementation which is made available to simplify later augmentation of the system.” The next entry is a brief description and reference for the Hough technique, which is defined as “a method of detecting parametric image features….” The self-contained definitions are somewhat shorter and perhaps less well-accepted than the abstracts that reference other works. On page 27 the definition of breadth-first parsing contains the statement that it is the “opposite” of depth-first parsing. This seems to take a narrow view of the possible traversal techniques. Many of the brief abstracts are extraordinarily clear and concise statements of complex concepts. This volume will serve well as a reference as persons from one area of AI encounter in-depth material from another area. Beginning students of AI will also find it useful because of the quality of its references to the classic works in the field.