"The DENDRAL computer program uses established rules of molecular fragmentation to help chemists solve complex structural problems from mass spectral data. This paper describes a computer program called Meta-DENDRAL, that can aid in the discovery of such rules from empirical data on known components. The program uses heuristic methods to search for common structural environments around those bonds that are found to fragment and abstracts plausible fragmentation rules. The program has been tested on the well-characterized, low-resolution mass spectra of aliphatic amines and the high-resolution mass spectra of estrogenic steroids. The program has also discovered new fragmentation rules for mono-, di-, and triketoandrostanes."Journal of the American Chemical Society 98:6168-6178

In L. Steels (Ed.), Advances in natural language processing. Antwerp, Belgium: University of Antwerp.

Research Report No. 25, Edinburgh: Department of Artificial Intelligence, August 1976.

Abstract: A data base system that supports natural language queries is not really natural if it requires the user to know how the data are represented. This paper defines a formalism, called conceptual graphs, that can describe data according to the user’s view and access data according to the system’s view. In addition, the graphs can represent functional dependencies in the data base and support inferences and computations that are not explicit in the initial query.IBM Journal of Research and Development 20:4, pp. 336-357.

Artificial Intelligence 7:21-49.

SRI Tech. Note 131, AI Center, SRI International, Inc., Menlo Park, Calif.

Zeitschrift fur Operations Research, Serie A, 20 (5), 203-208.

The alpha-beta technique for searching game trees is analyzed, in an attempt to provide some insight into its behavior. The first portion of this paper is an expository presentation of the method together with a proof of its correctness and a historical discussion. The alpha-beta procedure is shown to be optimal in a certain sense, and bounds are obtained for its running time with various kinds of random data.

This report describes progress in the development of an interactive computer program, termed MYCIN, that uses the clinical decision criteria of experts to advise physicans who request advice regarding selection of appropriate antimicrobial therapy for hospital patients with bacterial infections. Since patients with infectious diseases often require therapy before complete information about the organism becomes available, infectious disease experts have identified clinical and historical criteria that aid in the early selection of antimicrobial therapy. MYCIN gives advice in this area by means of three subprograms: (1) A Consultation System that uses information provided by the physician, together with its own knowledge base, to choose an appropriate drug or combination of drugs; (2) An Explanation System that understands simple English questions and answers them in order to justify its decisions or instruct the user; and (3) A Rule Acquisition System that acquires decision criteria during interactions with an expert and codes them for use during future consultation sessions. A variety of human engineering capabilities have been included to heighten the program's acceptability to the physicians who will use it. Early experience indicates that a sample knowledge base of 200 decision criteria can be used by MYCIN to give appropriate advice for many patients with bacteremia.

Latin, Greek, Russian, Turkish, German) the relationship of a noun phrase to the rest of a sentence is indicated by altered forms of the noun. The possible relationships are called (surface) “cases”. Because (1) it is difficult to specify semantic-free selection rules for the cases, and (2) related phenomena based on prepositions or word order appear in apparently case-less languages, many have argued that studies of cases should focus on meaning, i.e. on “deep cases”. Deep cases bear a close relationship to the modifiers of a concept. In fact, one could consider a deep case to be a special, or distinguishing, modifier.