Computers and Thought Lecture: The Ubiquity of Discovery

Abstract As scientists interested in studying the phenomenon of “intelligence”, we first choose a view of Man, develop a theory of how intelligent behavior is managed, and construct some models which can test and refine that theory. The view we choose is that Man is a processor of symbolic information . The theory is that sophisticated cognitive tasks can be cast as searches or explorations, and that each human possesses (and efficiently accesses) a large body of informal rules of thumb (or heuristics ) which constrain his search. The source of what we colloquially call “intelligence” is seen to be very efficient searching of an a priori immense space. Some computational models which incorporate this theory are described. Among them is AM , a computer program that develops new mathematical concepts and formulates conjectures involving them; AM is guided in this exploration by a collection of 250 more or less general heuristic rules. The operational nature of such models allows experiments to be performed upon them, experiments which help us test and develop hypotheses about intelligence. One interesting finding has been the ubiquity of this kind of heuristic guidance: intelligence permeates everyday problem solving and invention, as well as the kind of problem solving and invention that scientists and artists perform. The ultimate goals of this kind of research are (i) to de-mystify the process by which new science and art are created, and (ii) to build tools (computer programs) which enhance man's mental capabilities.