"Among the new languages for instructing computers is a remarkable one called LISP. The name comes from the first three letters of LIST and the first letter of PROCESSING. Not only is LISP a language for instructing computers but it is also a formal mathematical language, in the same way as elëmentary algebra when rigorously defined and used is a formal mathematical language.The LISP language and its implementation on the IBM 7090 computer were worked out by a group including John McCarthy, Stephen B. Russell , Daniel J. Edwards, Paul W. Abrahams, Timothy P. Hart, Michael I. Levin, Marvin L. Minsky, and others.LISP is designed primarily for processing data consisting of lists of symbols. It has been used for symbolic calculations in differential and integral calculus, electrical circuit theory, mathematical logic , game playing, and other fields of intelligent handling of symbols."Information International, Inc, Cambridge, Mass.

"It is well known to be impossible to tile with dominoes a checkerboard with two opposite corners deleted. This fact is readily stated in the first order predicate calculus, but the usual proof which involves a parity and counting argument does not readily translate into predicate calculus. We conjecture that this problem will be very difficult for programmed proof procedures."Stanford Artificial Intelligence Project Memo No. 16

This paper describes a trial-and-error device which learns to play the game of Noughts and Crosses. It was initially constructed from matchboxes and coloured beads and subsequently simulated in essentials by a program for a Pegasus 2 computer. The parameters governing the adaptive behaviour of this automaton are described and preliminary observations on its performance are briefly reported.

A statement in a spoken language may be regarded as a one-dimensional string of symbols used to communicate an idea from the speaker to a listener. The dimensionality of the statement is limited by the need for presenting words in a single time sequence. However, evidence indicates that most information and ideas are not stored by people in one-dimensional arrays isomorphic to these linear strings. This implies that a speaker must use certain complex information manipulating processes to transform the stored information to a linear output string, and that a listener, in order to "understand" the speaker, must use another set of processes to decode this linear string. In order for communication to take place, the information map of both the listener and the speaker must be approximately the same, at least for the universe of discourse.

"This report describes some experiments in constructing a compiler that makes use of heuristic problem~solving techniques such as those incorporated in the General Problem Solver (GPS). The experiments were aimed at the dual objectives of throwing light on some of the problems of constructing more powerful programming languages and compilers, and of testing whether the task of writing a computer program can be regarded as a "problem" in the sense in which that term is used in GPS. The present paper is concerned primarily with the second objective--with analyzing some of the problem-solving processes that are involved in writing computer programs. At the present stage of their development, no claims will be made for the heuristic programming procedures described here as practical approaches to the construction of compilers. Their interest lies in what they teach us about the nature of the programming task." JACM, 10, 493-506. See also: Artificial intelligence and self-organizing systems: Experiments with a Heuristic Compiler. (http://dl.acm.org/citation.cfm?id=806076)

Use the link below to share a full-text version of this article with your friends and colleagues.

We wish to acknowledge the helpful suggestions and encouragement of Herbert Simon, Edward Feigenbaum, Julian Feldman, Frank Marzocco, and Charles Baker. Thanks are also due the Committee on Simulation of Cognitive Processes of the Social Science. Use the link below to share a full-text version of this article with your friends and colleagues.

Article based on Ph.D. dissertation at Carnegie Tech. "... the problem of meaning is of major importance in the study of the nature of intelligence, and that a useful definition of meaning must include not only denotation but connotation and implication as well. To handle these important questions it is necessary to study cognitive organizations which are more complex than those upon which most psychological theories are based. A central question is the storage of large numbers of interrelated propositions in a manner which efficiently uses memory capacity." In E.A. Feigenbaum & J. Feldman (Eds.) Computers and Thought, pp. 217-233. McGraw-Hill, 1963.

E.A. Feigenbaum and J. Feldman (Eds.). Computers and Thought. McGraw-Hill, 1963. This collection includes twenty classic papers by such pioneers as A. M. Turing and Marvin Minsky who were behind the pivotal advances in artificially simulating human thought processes with computers. All Parts are available as downloadable pdf files; most individual chapters are also available separately. COMPUTING MACHINERY AND INTELLIGENCE. A. M. Turing. CHESS-PLAYING PROGRAMS AND THE PROBLEM OF COMPLEXITY. Allen Newell, J.C. Shaw and H.A. Simon. SOME STUDIES IN MACHINE LEARNING USING THE GAME OF CHECKERS. A. L. Samuel. EMPIRICAL EXPLORATIONS WITH THE LOGIC THEORY MACHINE: A CASE STUDY IN HEURISTICS. Allen Newell J.C. Shaw and H.A. Simon. REALIZATION OF A GEOMETRY-THEOREM PROVING MACHINE. H. Gelernter. EMPIRICAL EXPLORATIONS OF THE GEOMETRY-THEOREM PROVING MACHINE. H. Gelernter, J.R. Hansen, and D. W. Loveland. SUMMARY OF A HEURISTIC LINE BALANCING PROCEDURE. Fred M. Tonge. A HEURISTIC PROGRAM THAT SOLVES SYMBOLIC INTEGRATION PROBLEMS IN FRESHMAN CALCULUS. James R. Slagle. BASEBALL: AN AUTOMATIC QUESTION ANSWERER. Green, Bert F. Jr., Alice K. Wolf, Carol Chomsky, and Kenneth Laughery. INFERENTIAL MEMORY AS THE BASIS OF MACHINES WHICH UNDERSTAND NATURAL LANGUAGE. Robert K. Lindsay. PATTERN RECOGNITION BY MACHINE. Oliver G. Selfridge and Ulric Neisser. A PATTERN-RECOGNITION PROGRAM THAT GENERATES, EVALUATES, AND ADJUSTS ITS OWN OPERATORS. Leonard Uhr and Charles Vossler. GPS, A PROGRAM THAT SIMULATES HUMAN THOUGHT. Allen Newell and H.A. Simon. THE SIMULATION OF VERBAL LEARNING BEHAVIOR. Edward A. Feigenbaum. PROGRAMMING A MODEL OF HUMAN CONCEPT FORMULATION. Earl B. Hunt and Carl I. Hovland. SIMULATION OF BEHAVIOR IN THE BINARY CHOICE EXPERIMENT Julian Feldman. A MODEL OF THE TRUST INVESTMENT PROCESS. Geoffrey P. E. Clarkson. A COMPUTER MODEL OF ELEMENTARY SOCIAL BEHAVIOR. John T. Gullahorn and Jeanne E. Gullahorn. TOWARD INTELLIGENT MACHINES. Paul Armer. STEPS TOWARD ARTIFICIAL INTELLIGENCE. Marvin Minsky. A SELECTED DESCRIPTOR-INDEXED BIBLIOGRAPHY TO THE LITERATURE ON ARTIFICIAL INTELLIGENCE. Marvin Minsky.

In A. C. Hoggatt and F. E. Balderston (Eds.), Symposium on simulation models: Methodology and applications to the behavioral sciences. Cincinnati: South-Western Publishing, 111-138.