In his new book "Alternate Realities: Mathematical Models of Nature and Man (New York: John Wiley and Sons, 1989, 493 pages, $34.95), John L. Casti gives us an impressive, up-to-date look at several areas of mathematics that are being applied to the study of biological and sociological systems.

The author makes an important scientific contribution to the theory of knowledge and automatic decision making. The book will be a reference on fundamental research as well as a useful instrument for scientists, philosophers, and advanced students. The book's structure is constructive, facilitating a clear transmission of the author's ideas. Bacchus uses two plans of exposition: the epistemological plan justifies his theory in a wide, philosophical perspective, and the formal, mathematical plan gives the reader a valuable instrument. The book may be too short to fulfill the author's goals, but it reports a research result and requires the reader to take a good look at the bibliography.

We consider two approaches to giving semantics to first-order logics of probability. The first approach puts a probability on the domain, and is appropriate for giving semantics to formulas involving statistical information such as “The probability that a randomly chosen bird flies is greater than 0.9.” The second approach puts a probability on possible worlds, and is appropriate for giving semantics to formulas describing degrees of belief such as “The probability that Tweety (a particular bird) flies is greater than 0.9.” We show that the two approaches can be easily combined, allowing us to reason in a straightforward way about statistical information and degrees of belief. We then consider axiomatizing these logics.

The output is assembly code for the Berkeley Abstract Machine (BAM). Directives hold starting from the next predicate that is input. Clauses do not have to be contiguous in the input stream, however, the whole stream is read before compilation starts. This manual is organized into ten sections.

In Proc. Workshop on Algorithmic Learning Theory, pp. 368–381.

To read the book "Automated Reasoning: Thirty-Three Basic Research problems (Prentice Hall, Englewood Cliffs, N.J., 1987, 300 pp., $11.00) by Larry Was it is not necessary to be an expert in mathematics or logic or computer science. However, even if you are such an expert, you will read it with interest, and likely, with enjoyment.

To read the book "Automated Reasoning: Thirty-Three Basic Research problems (Prentice Hall, Englewood Cliffs, N.J., 1987, 300 pp., $11.00) by Larry Was it is not necessary to be an expert in mathematics or logic or computer science. However, even if you are such an expert, you will read it with interest, and likely, with enjoyment.

McDermott makes some valid points in his review ... It's too bad that he chose to embed the helpful comments in the context of his by-now-tiresome doubts about the value of logic in AI.

The book "Logical Foundations of Artificial Intelligence (Morgan Kaufmann, Los Altos, Calif., 1987, 406 pp., $48.95) by Michael Genesereth and Nils Nilsson is about declarative knowledge.

Commentators on AI converge on two goals they believe define the field: (1) to better understand the mind by specifying computational models and (2) to construct computer systems that perform actions traditionally regarded as mental. We should recognize that AI has a third, hidden, more basic aim; that the first two goals are special cases of the third; and that the actual technical substance of AI concerns only this more basic aim. This third aim is to establish new computation-based representational media, media in which human intellect can come to express itself with different clarity and force. This article articulates this proposal by showing how the intellectual activity we label AI can be likened in revealing ways to each of five familiar technologies.