D.Michie (Ed.), Expert systems in the micro- electronic age.Edinburgh: Edinburgh University Press, 153-167

A program called "AM" is described which carries on simple mathematics research,defining and studying new concepts under the guidance of a large body ofheuristic rules. The 250 heuristics communicate via an agenda mechanism, aglobal priority queue of small tasks for the program to perform, and reasons whyeach task is plausible (for example, "Find generalizations of 'primes', because'primes' turned out to be so useful a concept"). Each concept is represented asan active, structured knowledge module. One hundred very incomplete modulesare initially supplied, each one corresponding to an elementary set-theoreticconcept (for example, union). This provides a definite but immense space whichAM begins to explore. In one hour, AM rediscovers hundreds of common concepts(including singleton sets, natural numbers, arithmetic) and theorems (for example,unique factorization).Summary of Ph.D. dissertation.Hayes, J.E., D. Michie, and L. I. Mikulich (Eds.), Machine Intelligence 9, Ellis Horwood.

Technometrics, 21(2)

In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 13). New York: Academic Press, 277-318

Academic Press.

"Computing can change our ways of thinking about many things, mathematics, biology, engineering, administrative procedures, and many more. But my main concern is that it can change our thinking about ourselves: giving us new models, metaphors, and other thinking tools to aid our efforts to fathom the mysteries of the human mind and heart. The new discipline of Artificial Intelligence is the branch of computing most directly concerned with this revolution. By giving us new, deeper, insights into some of our inner processes, it changes our thinking about ourselves. It therefore changes some of our inner processes, and so changes what we are, like all social, technological and intellectual revolutions." This book, published in 1978 by Harvester Press and Humanities Press, has been out of print for many years, and is now online, produced from a scanned in copy of the original, digitised by OCR software and made available in September 2001. Since then a number of notes and corrections have been added. Atlantic Highlands, NJ: Humanities Press.

AI Journal 11(1,2):115— 154. Reprinted in Clancey & Shortliffe, Ch.9.

IEEE Transactions on Automatic Control, 23 (2), 298-304.

"The terms adaptation, learning, concept-formation, induction, self-organization, and self-repair have all been used in the context of learning system (LS) research. The research has been conducted within many different scientific communities, however, and these terms have come to have a variety of meanings. It is therefore often difficult to recognize that problems which are described differently may in fact be identical. Learning system models as well are often tuned to the require- ments of a particular discipline and are not suitable for application in related disciplines."In Encyclopedia of Computer Science and Technology, Vol. 11. Dekker

"A CASNET model consists of three main components: observations of a patient, pathophysiological states, and disease classifications. As observations are recorded, they are associated with the appropriate intennediate states. These states, in turn, are typically causally related, thereby forming a network that summarizes the mechanisms of disease. It is these patterns of states in the network that are linked to individual disease classes." Artificial intelligence, August, 1978. Reprinted in Clancey & Shortliffe. Readings in Medical Artificial Intelligence: The First Decade. Ch. 7.