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.

David E. Rumelhart Donald A. Norman Department of Psychology University of California, San Diego La Jolla, California 92037 Abstract A general system to simulate human cognitive processes is described. The four-part system comprises a nodespace to store the network structure; a supervisor; a transition network parser; and an interpreter. The method by which noun phrases operate and the process for the determiner "the" is presented. An analysis of verb structures illustrates how network structures can be constructed from primitive verb definitions that get at the underlying structures of particular verbs. The paper concludes with an illustration of a problem in question-asking. A Model of Human Memory We have constructed a large general simulation of human language and long-term memory on the premise that the study of the interrelationships among psychological processes will lead to more insight into human cognition and memory. The general implementation is basically complete, and a variety of users are starting to study specific psychological tasks (language understanding; children's development of language; primitive verb structure; reading; inference; game playing--Go and Gomoku; visual representation and memory; learning; and question answering). It is still too early to report on the results of the psychological investigation.. Therefore, this paper is a progress report on the system and the underlying psychological principles. The major guidelines have come from our attempts to represent long-term memory structures. We know that people rapidly forget the details about the surface structure of an experience but retain the meaning or interpretation of that experience indefinitely.

"A program that achieves the interpretation of line drawings as polyhedral scenes is described. The method is based on general coherence rules that the surfaces and edges must satisfy, thereby avoiding the use of predetermined interpretations of particular categories of picture junctions and corners." The paper also comments on the relationship of this program to four other scene analysis programs.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California. Revised version in Artificial Intelligence 4:121-137.

Additive AND/OR graphs are defined as AND/ /ORgraphs without circuits, which can be considered as folded AND/OR trees; i.e. the cost of a common subproblem is added to the cost as many times as the subproblem occurs, but it is computed only once. Additive AND/OR graphs are naturally obtained by reinterpreting the dynamic programming method in the light of the problem-reduction approach. An example of this reduction is given. A top-down and a bottom-up method are proposed for searching additive AND/OR graphs. These methods are, respectively, extensions of the "arrow" method proposed by Nilsson for searching AND/OR trees and Dijkstra's algorithm for finding the shortest path. A proof is given that the two methods find an optimal solution whenever a solution exists. 1) introduction In the literature on artificial intelligence, AND/OR trees have proved to be a good formalism for representing the problem-reduction approach to problem solving. Usually, the search is for any solution tree, but in a paper by Nilsson the problem is presented of finding the best solution tree, where arcs have a given cost, and the cost of a tree is simply the sum of the costs of the arcs. Nilsson gives there an algorithm which assumes available, for each node, an estimate of the cost of the "optimal solution tree rooted at that node.

In one major section we discuss the imprecision, the incompleteness, the openendedness, and the uncertainty of people's knowledge. In the other major section we discuss strategies people use to make different types of deductive, negative, and functional inferences, and the way uncertainties combine in these inferences. Keywords Semantics, inference, cognitive processes, natural language processing, human memory, question-answering systems, deduction, analogy 1. Introduction In this paper we will discuss how to represent and process information in a computer in ways that are natural to people. This does not mean doing away completely with representations and procedures which computers have traditionally used, but adding new representations and procedures which they have not used. People often store and communicate imprecise, incomplete, and unquantified information; they often assert truth or falsity in relative terms; and they seldom seem to use rigorous logic in their inferential processes. Because of these conditions, people seem to have an almost infinite information processing capacity, with inference making and problem solving abilities more refined and far more flexible than any existing computer program. How can we study these human capabilities in order to make our machines show similar performance? A combination of approaches is perhaps best. Observation of people's behavior, introspection, some experimentation, protocol analysis, and synthesis of computer programs can all be valuable techniques.

A Universal Modular ACTOR Formalism for Artificial Intelligence Carl Hewitt Peter Bishop Richard Steiger Abstract This paper proposes a modular ACTOR architecture and definitional method for artificial intelligence that is conceptually based on a single kind of object: actors [or, if you will, virtual processors, activation frames, or streams]. The formalism makes no presuppositions about the representation of primitive data structures and control structures. Such structures can be programmed, micro-coded, or hard wired 1n a uniform modular fashion. In fact it is impossible to determine whether a given object is "really" represented as a list, a vector, a hash table, a function, or a process. The architecture will efficiently run the coming generation of PLANNERlike artificial intelligence languages including those requiring a high degree of parallelism. The efficiency is gained without loss of programming generality because it only makes certain actors more efficient; it does not change their behavioral characteristics. The architecture is general with respect to control structure and does not have or need goto, interrupt, or semaphore primitives. The formalism achieves the goals that the disallowed constructs are intended to achieve by other more structured methods. PLANNER Progress "Programs should not only work, but they should appear to work as well." PDP-1X Dogma The PLANNER project is continuing research in natural and effective means for embedding knowledge in procedures. In the course of this work we have succeeded in unifying the formalism around one fundamental concept: the ACTOR. Intuitively, an ACTOR is an active agent which plays a role on cue according to a script" we" use the ACTOR metaphor to emphasize the inseparability of control and data flow in our model. Data structures, functions, semaphores, monitors, ports, descriptions, Quillian nets, logical formulae, numbers, identifiers, demons, processes, contexts, and data bases can all be shown to be special cases of actors. All of the above are objects with certain useful modes of behavior. Our formalism shows how all of the modes of behavior can be defined in terms of one kind of behavior: sending messages to actors. An actor is always invoked uniformly in exactly the same way regardless of whether 1t behaves as a recursive function, data structure, or process.

"A five-year interdisciplinary effort by speech scientists and computer scientists has demonstrated the feasibility of programming a computer system to “understand” connected speech, i.e., translate it into operational form and respond accordingly. An operational system (HARPY) accepts speech from five speakers, interprets a 1000-word vocabulary, and attains 91 percent sentence accuracy. This Steering Committee summary report describes the project history, problem, goals, and results." Amsterdam: North- Holland.

The aim of this paper is to present in a rigorous way the syntax and semantics of a certain fragment of a certain dialect of English. Patrick Suppes claims, in a paper prepared for the present workshop [the 1970 Stanford Workshop on Grammar and Semantics], that at the present time the semantics of natural languages are less satisfactorily formulated than the grammars ¼ [and] a complete grammar for any significant fragment of natural language is yet to be written.'' This claim would of course be accurate if restricted in its application to the attempts emanating from the Massachusetts Institute of Technology, but fails to take into account the syntactic and semantic treatments proposed in Montague (1970a, b). Thus the present paper cannot claim to present the first complete syntax (or grammar, in Suppes' terminology) and semantics for a significant fragment of natural language; and it is perhaps not inappropriate to sketch relations between the earlier proposals and the one given below. Montague (1970b) contains a general theory of languages, their interpretations, and the inducing of interpretations by translation.

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."

Proceedings of the international conference on computational linguistics, Pisa, Italy.