Born 11 November,
Open Classical Scholarship to
1942 - 1945
War service in the Foreign
Pre-clinical medical school,
M A (Oxon) in Human Anatomy and Physiology.
D Phil (Oxon) in Mammalian Genetics.
1952 - 1958
Research Associate, Department of
Scientific Fellow of the
Zoological Society of
Senior Lecturer in Surgical
Reader in Surgical Science, Edinburgh.
Author (jointly): An Introduction to Molecular Biology.
Founder and Director,
Experimental Programming Unit, Edinburgh.
Royal Society Lecturer in the
Personal Chair of Machine
Founder and first Chairman,
Department of Machine Intelligence and Perception,
Author: Computer Programming for
Schools:first steps in Algol,
Edinburgh: Oliver & Boyd (with A. Ortony and R.M. Burstall).
Fellow of the Royal Society of
Co-founder and first Board Chairman,
Edinburgh University Centre for Industrial Consultancy and Liaison.
D Sc (Oxon) in Biological
Fellow of the British Computer Society.
William Withering Lectures,
1974 - 1984
Director, Machine Intelligence Research Unit, Edinburgh.
Author: On Machine Intelligence
(2nd ed. 1986).
G A Miller Lectures,
1975 - 1984
Chairman of the Board of Trustees, A M Turing Trust.
Herbert Spencer Lecture,
Samuel Wilks Memorial Lecture,
Editor: Expert Systems and the Micro-electronic Age.
Author: Machine Intelligence and
Evening Discourse, The Royal Institution,
Editor (jointly): Intelligent
Systems: the Unprecedented Opportunity.
G A Miller Lecture,
Author (jointly): The Creative
Technology Lecture, The Royal Society of
Professor Emeritus of Machine Intelligence,
Founder and Director of Research, the Turing Institute,
Chief Scientist, the Turing Institute.
Pioneer Award of the International
Embryo Transfer Society
(jointly, for work in the 1950's with Dr Anne McLaren).
Honorary Life Membership of the BCS Specialist Group on Expert Systems.
S L A Marshall Lecture, US Army
Inst. for the Behav. and Social Sciences,
Elected a Founding Fellow of the American Association for Artificial Intelligence.
Hon D Sc, National Council for
C C Garvin Lecture, Virginia
Polytechnic Institute and
Hon D Sc,
Editor (jointly). Machine Learning, Neural and Statistical Classification, Ellis Horwood Ltd.
Visitor, AI Applications Institute,
Founder and Treasurer of the Human-Computer Learning Foundation.
Associate Member of the Josef Stefan Institute of
Achievement Medal of the
Feigenbaum Medal of the World
Congress on Expert Systems.
Hon D Univ,
Hon. D.Sc. University of
Foreign Honorary Member,
IJCAI Award for Research Excellence.
Foreign Honorary Member,
Lifetime Achievement Award – British Computer Society Specialist Group on Artificial Intelligence.
Professor Michie's publications include four books and about 170 papers in experimental biology, AI and computing. He was Editor in Chief of the Machine Intelligence series (nineteen volumes since 1967).
His innovations in computer learning had been sparked by discussions with Alan Turing during and immediately after the war. In his February 1947 lecture to the London Mathematical Society, delivered before the first stored-program machines were operational, Turing sketched the basic idea. He argued that a computer program, when such a thing existed, could be enabled to improve its performance through its own accumulating experience. Michie began his first experiments in 1960. His tic-tac-toe machine MENACE demonstrated the basic principle of a self-reinforcing learning mechanism. MENACE employed Michie's conceptually simple general-purpose learning algorithm BOXES which could also discover robust control strategies for the pole-and-cart problem, but was soon employed industrially to evolve strategies for automatic control, such as controlling a steel mill.
Michie's next move in computer learning was to develop and systematize techniques for inductively extracting machine-executable concepts from example data. Michie showed how to circumvent the "Feigenbaum bottleneck" in expert systems development - the elicitation through dialog of (often intuitive) human expertise, arduous and often near-impossible to articulate.
Stimulated by Michie's guidance at
Using this more user-oriented approach, Michie and his students repeatedly reduced previously intractable problem-domains (e.g. constructing large bodies of chess endgame knowledge previously unknown to grandmasters), including numerous industrial problems. The resulting machine-generated solution-programs explained the rationale of their own decisions, providing more comprehensive, more precise and deeper answers than those from human experts. Notable examples were:
In 1968 Michie had already encapsulated rote-learning as a generic library facility, drawing together the seemingly disconnected principles and techniques of machine learning, and embedding them in the defined procedures of a programming language. With these "memo functions" , also referred to as "function caching", Michie made novel use of the fact that every computable function has both a tabular and an algorithmic representation. Under the memo-function regime, executable function procedures automatically and incrementally speeded themselves up by storing the results of functions for later reuse, rather than recomputing them. Memo functions were added to the library of the POP-2 programming system and later worked into POP-2 itself and into LISP. Thus self-optimising capabilities were made available to programmers for any integer-values function procedure that they cared to implement.
Memo functions were also employed to crucial effect in the early 1970s