Methods of Information in Medicine, 12: 45-51. Reprinted in Clancey & Shortliffe, Ch.2

Abduction is a basic form of logical inference, which is said to engender the use of plans, perceptual models, intuitions, and analogical reasoning - all aspects of Intelligent behavior that have so far failed to find representation in existing formal deductive systems. This paper explores the abductive reasoning process and develops a model for it s mechanization, .which consists of an embedding of deductive logic in an iterative hypothesis and test procedure. An application of the method to the problem of medical diagnosis is discussed.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

This paper describes the structure and operation of the Hearsay speech understanding system by the use of a specific example illustrating the various stages of recognition. The system consists of a set of cooperating independent processes, each representing a source of Knowledge. The knowledge is used either to predict what may appear in a given context or to verify hypotheses resulting from a prediction. The structure of the system is illustrated by considering its Operation in a particular task situation: Voice-Chess. The representation and use of various sources of knowledge are outlined. Preliminary results of the reduction in search resulting from the use of various sources of knowledge are given.See also: IEEE Transactions on Computers C-25:427-431.(1976).In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

At the present stage of research in artificial intelligence , machines are stil l remote from achieving a level of intelligence comparable in complexity to human thought. As computer applications become more sophisticated, however, and thus more influential in human affairs , it becomes increasingly important to understand both the capabilities and limitations of machine Intelligence and its potential impact on society. To this end, the artificial intelligence field was ex­amined in a systematic manner. The study was divided into two parts : (1) Delineation of areas of artificial intelligence, and postulatio " of hypothetical prod­ucts resulting from progress in the field , and (2) A judgmental portion, which involved appli­cations and implications of the products to society . For the latter purpose, a Delphi study was conducted among experts in the artificial intelligence field to solicit their opinion concerning prototype and com­mercial dates for the products, and the possibility and desirability of their applications and implications .In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

IJCAI S, 23-29.

A versatile assembly system, using TV cameras and oomputer-controlled arm and moving table, is described. It makes almple assemblies such aa a peg and rings and a toy car. It separates parts from a heap, recognising them with an overhead camera, then assembles them by feel. It can be instructed to perform a new task with different parte by spending an hour showing it the parts and a day or two programming the assembly manipulations. A hierarchical description of parts, views, outlines etc. is used to construct models, and a structure matching algorithm is used in recognition.Later version appearing in Artificial Intelligence, Vol 6, pp. 129(1975) (available for a fee).In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

The design of application of artificia l intelli­gence to a scientific task such as Organic Chemical Synthesis was the topic of a Doctoral Thesis completed in the summer of 197I. Chemical synthesis in practice involves i) the choice of molecule to be synthesized; i i) the formulation and specification of a plan for synthesis (involving a valid reaction pathway leading from commercial or readily available compounds to the target compounds with consideration of feasibility regarding the purposes of synthesis);iii ) the selection of specific individual steps of reaction and their temporal ordering for execution; iv) the exper­imental execution of the synthesis and v) the redesign of syntheses, if necessary, depending upon the exper­imental results. In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

Since 1967 there has again been great interest in chess programming. This paper demonstrates that the structure of today's most successful programs cannot be extended to play Master level chess. Certain basic requirements of a Master player's performance are shown to be outside the performance limits to which a program of this type could be extended. The paper also examines a basic weakness in the tree-searching model approach when applied to situations that cannot be searched to completion. This is the Horizon Effect, which causes unpredictable evaluation errors due to an interaction between the static evaluation function and the rules for search termination. The outline of a model of chess playing that avoids the Horizon Effect and appears extendable to play Master level chess is presented, together with some results already achieved In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California, pp. 77-85

This paper considers various factors affecting system organization for speech understanding research. The structure of the Hearsay system based on a set of cooperating, independent processes using the hypothesize-and-test paradigm is presented. Design considerations for the effective use of multiprocessor and network architectures in speech understanding systems are presented: control of processes, interprocess communication and data sharing, resource allocation, and debugging are discussed.See also: IEEE Xplore.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

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."