Reprinted in Readings in Uncertain Reasoning, G. Shafer and J. Pearl, eds., pp. 259-273, San Mateo, CA: Morgan Kaufmann Publishers, Inc., 1990.See also: Stanford Center for Biomedical Informatics Research (BMIR).… quantifying confirmation and then manipulating the numbers as though they were probabilities quickly leads to apparent inconsistencies or paradoxes. Carl Hempel presented an early analysis of confirmation (Hempel, 1965), pointing out as we have that C[h,e] is a very different concept from P(hle ). His famous Paradox of the Ravens was presented early in his discussion of the logic of confirmation. Let hl be the statement that "all ravens are black" and h2 the statement that "all nonblack things are nonravens." Clearly hi is logically equivalent to h,2. If one were to draw an analogy with conditional probability, it might at first seem valid, therefore, to assert that C[hl,e] = C[h2,e] for all e. However, it appears counterintuitive to state that the observation of a green vase supports hi, even though the observation does seem to support h,2. C[h,e] is therefore different from P(hle) for it seems somehow wrong that an observation of a vase could logically support an assertion about ravens. Another characteristic of a quantitative approach to confirmation that distinguishes the concept from probability was well-recognized by Carnap (1950) and discussed by Barker (1957) and Harrd (1970). They note it is counterintuitive to suggest that the confirmation of the negation of a hypothesis is equal to one minus the confirmation of the hypothesis, i.e., C[h,e] is not 1 - C[-qh,e]. The streptococcal decision rule asserted that a gram-positive coccus growing in chains is a Streptococcus with a measure of support specified as 7 out of 10. This translates to C[h,e]=0.7 where h is "the organism is a Streptococcus" and e is the information that "the organism is a gram-positive coccus growing in chains." As discussed above, an expert does not necessarily believe that C[mh,e] = 0.3. The evidence is said to be supportive of the contention that the organism is a Streptococcus and can therefore hardly also support the contention that the organism is not a Streptococcus. Ch.13 of Mycin Book; revised from Math. Biosci. 23:351-379

Computers and Biomedical Research, 8 (4): 303-320. Reprinted in Sheehy, N. and Capman, A.J., eds. The International Library of Critical Writings in Psychology: Cognitive Science, London: Edward Elgar Publishing Ltd., pp. 250-267, 1995. See also: Stanford HPP 75-2.

Artificial Intelligence 6:361-371

New York: American Elsevier

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

Artificial Intelligence 5:137-148.

"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.

In researc which lan uac; assumed knowled way it use of provide impreci recent h into a is to e. In that on re of th is used the cons s, to na se acous years, utomati (r,et a nost e need e lan u (pragma traints ke sens tic sit there has c speech u computer of this s to pro are (its s tics). It and expec e of the i nal that i been a nderstan to und recent a vide th yntax an will th tations nherentl s human rroat increase in dine, the purpose of erstand the spoken ctivity, it has been e computer with a d semantics) and the en be able to make which this knowledfre y vaf ue, sloppy and soeech. Syntactic constraints and expectations are based on the patterns formed by a Riven set of linguistic objects, e. .

In Schank and Colby, Computer Models of Thought and Language, San Francisco: Freeman, 1973, pp. 1-60

The first Mycin publication. An antimicrobial therapy consultation system has been developed which utilizes a flexible representation of knowledge. The novel design facilitates interactive advice-giving sessions with physicians. 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. Comput. Biomed. Res. 6:544-560.