John Wiley and Sons, Inc. Robinson, J.A. (1965) "A Machine Oriented Logic Based on the Resolution Principle".

Northwestern students who are interested in changing their major, or simply sampling the computer science field, can take individual introductory courses.

"With the objective of making into a science the art of verifying computer programs (debugging), the author addresses both practical and theoretical aspects of the process. A classic of sequential program verification, this volume has been translated into almost a dozen other languages and is much in demand among graduate and advanced undergraduate computer science students. Subjects include computability (with discussions of finite automata and Turing machines); predicate calculus (basic notions, natural deduction, and the resolution method); verification of programs (both flowchart and algol-like programs); flowchart schemas (basic notions, decision problems, formalization in predicate calculus, and translation programs); and the fixpoint theory of programs (functions and functionals, recursive programs, and verification programs). The treatment is self-contained, and each chapter concludes with bibliographic remarks, references, and problems." New York: McGraw-Hill, 1974.

This paper presents two new machine learning procedures used to arrive at “knowledgeable” static evaluators for checker board positions. The static evaluators are compared with each other, and with the linear polynomial used by Samuel [9], using two different numerical indices reflecting the extent to which they agree with the choices of checker experts in the course of tabulated book games. The new static evaluators are found to perform about equally well, despite the relative simplicity of the second; and they perform noticably better than the linear polynomial. An indication of the significance of the absolute values of these two numerical indices is provided by a discussion of a simple, purely heuristic, static evaluator, whose performance indices lie between those of the polynomial and those of the other two static evaluators.

British Medical Journal, 1, 376–380.

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An antimicrobial therapy consultation system has been developed which utilizes a flexible representation of knowledge. An ability to display reasons for making decisions at the request of the user permits the program to serve a tutorial as well as consultative role. The feasibility of the judgmental rule approach which the program uses has been demonstrated with a limited knowledge base of approximately 100 rules. Its ultimate success as a clinically useful tool depends upon acquisition of additional rules and thus upon co-operation of infectious disease experts willing to improve the program's knowledge base. The techniques for acquisition, representation, and utilization of knowledge, plus considerations of natural language processing, draw upon and contribute to current Artificial Intelligence research.

In recent years many attempts have been made to use the computer as an aid to diagnosis, but little has been done to exploit the potential of computer technology as a more general aid to decision making. We describe the use of the discipline of decision analysis as the basis for an experimental interactive computer program designed to assist the physician in the clinical management of acute oliguric renal failure. The program deals with alternative courses of action, either tests or treatments, for which the potential risks or benefits may be large, and it balances the anticipated risk of a given strategy against the anticipated benefit that it offers the patient. The appraisals of the different courses of action open to the physician are expressed in quantitative terms as expected value. The program has been evaluated by comparing its recommendations to those of experienced nephrologists in 18 simulated cases of acute oliguric renal failure.

Kenneth Mark Colby, 1920 - 2001 Kenneth Colby was born in Waterbury, Connecticut and graduated from Yale in 1941. Two years later he graduated from Yale's School of Medicine. Colby started his career as a professor of computer science at Stanford, and also did some research for the National Institute of Mental Health. It was there that he created Parry in the university's Artificial Intelligence Library. Parry was a chatterbot, and able to have conversations with people.

Dept. of Computer Science, Carnegie-Mellon University. "Many game-playing programs must search very large game trees. Use of the alpha-beta pruning algorithm instead of the simple minimax search reduces by a large factor the number of bottom positions which must be examined in the search. An analytical expression for the expected number of bottom positions examined in a game tree using alpha-beta pruning is derived, subject to the assumptions that the branching factor N and the depth D of the tree are arbitrary but fixed, and the bottom positions are a random permutation of ND unique values. A simple approximation to the growth rate of the expected number of bottom positions examined is suggested, based on a Monte Carlo simulation for large values of N and D. The behavior of the model is compared with the behavior of the alpha-beta algorithm in a chess playing program and the effects of correlation and non-unique bottom position values in real game trees are examined."