Machine Intelligence 1 (1967) (eds N. Collins and D. Michie) Oliver & Boyd, Edinburgh Machine Intelligence 2 (1968) (eds E. Dale and D. Michie) Oliver & Boyd, Edinburgh (1 and 2 published as one volume in 1971 by Edinburgh University Press) (eds N. Collins, E. Dale, and D. Michie) Machine Intelligence 3 (1968) (ed. CLARENDON PRESS - OXFORD 1991 Oxford University Press, Walton Street, Oxford 0X2 6DP Oxford New York Toronto Delhi Bombay Calcutta Madras Karachi Petaling Jaya Singapore Hong Kong Tokyo Nairobi Dar es Salaam Cape Town Melbourne Auckland and associated companies in Berlin lbadan Oxford is a trade mark of Oxford University Press Published in the United States by Oxford University Press, New York C J. E. Hayes, D. Michie, and E. Tyugu, 1991 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of Oxford University Press British Library Cataloguing in Publication Data Machine intelligence. ISBN 0-19-853823-5 Library of Congress Cataloging in Publication Data Machine intelligence 12: towards an automated logic of human thought /edited by J. E. Hayes, D. Michie, and It is a pleasure to contribute an introduction to this twelfth volume of the international Machine Intelligence series. My own work has, at times, cast me in the scientific roles of experimenter, instrumentation designer, and administrator.

In this paper we will be concerned with such reasoning in its most general form, that is, in inferences that are defeasible: given more information, we may retract them. The purpose of this paper is to introduce a form of non-monotonic inference based on the notion of a partial model of the world. We take partial models to reflect our partial knowledge of the true state of affairs. We then define non-monotonic inference as the process of filling in unknown parts of the model with conjectures: statements that could turn out to be false, given more complete knowledge. To take a standard example from default reasoning: since most birds can fly, if Tweety is a bird it is reasonable to assume that she can fly, at least in the absence of any information to the contrary. We thus have some justification for filling in our partial picture of the world with this conjecture. If our knowledge includes the fact that Tweety is an ostrich, then no such justification exists, and the conjecture must be retracted.

Machine Intelligence 1 (1967) (eds N. Collins and D. Michie) Oliver & Boyd, Edinburgh Machine Intelligence 2 (1968) (eds E. Dale and D. Michie) Oliver & Boyd, Edinburgh (1 and 2 published as one volume in 1971 by Edinburgh University Press) (eds N. Collins, E. Dale, and D. Michie). CLARENDON PRESS OXFORD 1988 Oxford University Press, Walton Street, Oxford 0X2 6DP Oxford New York Toronto Delhi Bombay Calcutta Madras Karachi Petaling Jaya Singapore Hong Kong Tokyo Nairobi Dar es Salaam Cape Town Melbourne Auckland and associated companies in Berlin lbadan Oxford is a trade mark of Oxford University Press Published in the United States by Oxford University Press, New York J. E. Hayes, D. Michie, and J. Richards 1988 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of Oxford University Press British Library Cataloguing in Publication Data Machine Intelligence. Richard J. 006.3 ISBN 0-19-853718-2 Library of Congress Cataloging in Publication Data Data available Typeset and printed in Northern Ireland at The Universities Press (Belfast) Ltd. Held at intervals in Scotland, the first seven International Machine Intelligence Workshops spanning the period of 1965-71 were involved in developing the new subject internationally--in those early days mainly as a mid-Atlantic phenomenon.

The initial plan for LOGLISP [1] was simply that it would offer, within LISP, a Horn-clause relational programming facility akin to PROLOG. This it does, but with some differences from PROLOG, notably the use of a breadth-first, rather than depth-first, elaboration of the underlying tree of alternative linear proofs, and the consequent avoidance of explicit backtracking as a control mechanism. It was because of these differences that the facility was called LOGIC rather than PROLOG, which would have been misleading. The name LOGLISP then refers to the combined system: LOGIC LISP. It soon became apparent, however, that the main interest of LOGLISP lay rather in its (relatively crude, but genuine) attempt to merge the functional programming style of LISP with the relational programming style of LOGIC and PROLOG. This was done by introducing the notion of'Lisp-transforms' into LOGIC.

It is given by them without supporting analysis but with the statement that the bishops'cannot win if the weaker side can obtain a position similar to the above, but they win in most cases'. The second position, a win, is then given with a solution and a number of supporting variations extending to 14 moves. One or other of both positions is repeated in the subsequent literature up to 1983 (e.g.

It is a rich source of difficult and challenging problems which involve issues of knowledge representation, the analysis of natural language, and the automation of practical and common-sense reasoning.

This paper describes some work on automatically generating finite counterexamples in topology, and the use of counterexamples to speed up proof discovery in intermediate analysis, and gives some examples theorems where human provers are aided in proof discovery by the use of examples.

Work of the Soviet school (approximately half the book) in this explosively growing area of machine intelligence is thus made accessible for the first time to Western readers, in addition to the latest Western advances. The emergent theme of knowledge-representation is supported on the theoretical and experimental sides by recent work in inductive inference and theory-formation.

Intelligent Systems: Practice and Perspective Machine Intelligence, Editor-in-Chief: Donald Michie Volumes 1-7 are published by Edinburgh University Press and in the United States by Halsted Press (a subsidiary of John Wiley & Sons, Inc.) Volumes 8-10 are published by Ellis Horwood Ltd., Publishers, Chichester and in the United State by Halsted Press (a subsidiary of John Wiley & Sons, Inc.) ELLIS HORWOOD LIMITED Publishers - Chichester Halsted Press: a division of JOHN WILEY & SONS New York - Brisbane - Chichester - Toronto First published in 1982 by ELLIS HORWOOD LIMITED Market Cross House, Cooper Street, Chichester, West Sussex, P019 lEB, England The publisher's colophon is reproduced from James Gillison's drawing of the ancient Market Cross, Chichester. Q335 The Library of Congress cataloged this serial as follows -67-13648 ISBN 0-85312-431-0 (Ellis Horwood Limited) ISSN 0076-2032 ISBN 0-470-27323-2 (Halsted Press) Typeset in Press Roman by Ellis Horwood Limited. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the permission of Ellis Horwood Limited, Market Cross House, Cooper Street, Chichester, West Sussex, England. The year of the first MI Workshop, 1965, was a milestone for more reasons than one, not least for the appearance of a paper entitled "A machine-oriented logic based on the resoluton principle". It was appropriate and a cause for pleasure that the author of that paper, J. A. Robinson, was the opening contributor to the scientific proceedings of MI-10, held in November 1981 at Case Western Reserve University, Cleveland, USA.

Motor control systems are complex systems that process information. Orientation behaviour, posture control, and the manipulation of objects are examples of motor control systems which involve one or more sensory modality and various central neural processes, as well as effector systems and their immediate neuronal control mechanisms. Like all complex information processing systems, they must be analysed and understood at several different levels (see, e.g., Marr & Poggio 1977). At the lowest level there is the analysis of basic components and circuits, the neurons, their synapses, etc. At the other extreme, there is the study of the computations performed by the system -- the problems it solves and the ways that it solves them -- and the analysis of its logical organization in terms of its primary modules. Each of these levels of description, and those in-between, has its place in the eventual understanding of motor control by the nervous system. None is sufficient, nor is there any simple translation from one to another. A purely biophysical investigation, however exhaustive, can say nothing by itself about the information processing performed by the system, nor, on the other hand, can an understanding of the computational problem which the system solves lead directly to an understanding of the properties of the hardware. Two examples of motor control theories belonging to different levels will illustrate this point.