Newell, A.


Human problem solving

Classics

The aim of the book is to advance the understanding of how humans think. It seeks to do so by putting forth a theory of human problem solving, along with a body of empirical evidence that permits assessment of the theory.Englewood Cliffs, N.J.: Prentice-Hall





GPS, a program that simulates human thought

Classics

This article is concerned with the psychology of human thinking. It setsforth a theory to explain how some humans try to solve some simpleformal problems. The research from which the theory emerged is intimatelyrelated to the field of information processing and the construction of intelligentautomata, and the theory is expressed in the form of a computerprogram. The rapid technical advances in the art of programming digitalcomputers to do sophisticated tasks have made such a theory feasible.It is often argued that a careful line must be drawn between the attemptto accomplish with machines the same tasks that humans perform, andthe attempt to simulate the processes humans actually use to accomplishthese tasks. The program discussed in the report, GPS (General ProblemSolver), maximally confuses the two approaches—with-mutual"!benefit. Lerende Automaten, Munich: Oldenberg KG


IPL-V: Information Processing Language V Manual

Classics

The complete rules for coding in Information Processing Language-V (IPL-V), and the documentation of extensions incorporated since publication of the Information Processing Language-V Manual. A summary of extensions and the minor modifications to the language is contained in the final section. An index, a list of the basic IPL-V processes, and a full-scale copy of the coding sheet appear at the end of the Memorandum.See also: Google Books.Prentice·Hall, Englewood Cliffs, NJ.


Elements of a theory of human problem solving

Classics

A description of a theory of problem-solving in terms of information processes amenable for use in a digital computer. The postulates are: "A control system consisting of a number of memories, which contain symbolized information and are interconnected by various ordering relations; a number of primitive information processes, which operate on the information in the memories; a perfectly definite set of rules for combining these processes into whole programs of processing." Examples are given of how processes that occur in behavior can be realized out of elementary information processes. The heuristic value of this theory is pertinent to theories of learning, perception, and concept formation.Psychological Review, March, 65(3):151-166



The Processes of Creative Thinking

Classics

"We ask first whether we need a theory of creative thinking distinct from a theory of problem solving. Subject to minor qualifications, we conclude there is no such need -- that we call problem solving creative when the problems solved are relatively new and difficult. Next, we summarize what has been learned about problem solving by simulating certain human problem solving processes with digital computers. Finally, we indicate some of the differences in degreee that might be observed in comparing relatively creative with relative routine problem solving."RAND Corporation Paper P-1320, Santa Monica, Calif


Empirical Explorations with the Logic Theory Machine: A Case Study in Heuristics

Classics

This is a case study in problem-solving, representing part of a program of research on complex information-processing systems. We have specifieda system for finding proofs of theorems in elementary symbolic logic, and by programming a computer to these specifications, have obtained empirical data on the problem-solving process in elementary logic. The program is called the Logic Theory Machine (LT); it was devised to learn how it is possible to solve difficult problems such as proving mathematical theorems, discovering scientific laws from data, playing chess, or understanding the meaning of English prose.The research reported here is aimed at understanding the complexp rocesses (heuristics) that are effective in problem-solving. Hence, we are not interested in methods that guarantee solutions, but which require vastamounts of computation. Rather, we wish to understand how a mathematician, for example, is able to prove a theorem even though he does not know when he starts how, or if, he is going to succeed.Proceedings of the Western Joint Computer Conference, 15:218-239. Reprinted in Feigenbaum and Feldman, Computers and Thought (1963).