Review of "Problem-Solving Methods in Artificial Intelligence by Nils J. Nilsson", McGraw-Hill Pub.

This book is not a survey on theorem proving programs, but the description of a program developed from 1960 to 1965. In the first part there are some generalities on artificial intelligence, and in the second part, some logical explanations, necessary for the comprehension of the program. The third part describes the program. The program has three important features:-it is general. It can study more than one formal system. It receives as data the inference rules and the axioms of the formal system which it must study.-it is capable of invention. It can work without knowing the theorem to be proven. It tries to find interesting theorems; it has only the definition of the interest of a theorem.-it proves theorems, but also metatheorems which are new productions and meta-metatheorems which are new means to get productions. This feature has a great heuristic value. This textbook explains the theoretical ideas underlying problem-solving by heuristically guided, trial-and-error search processes. These search methods are explained by the use of a uniform vocabulary, and several theoretical results about the properties of heuristic search are presented. Several simple example problems, puzzles, and games are used to illustrate the techniques. The author refers to instances in which these same techniques have been successfully applied to problems much more complex than the example problems in his book. The book also includes three chapters that deal with resolution-based theorem-proving in the predicate calculus and its applications to problem solving. Each chapter contains exercises and a section on bibliographical and historical remarks that list some of the more important references related to the subject of the chapter.