B.RANDELL 3 PROGRAM PROOF AND MANIPULATION 2 Some techniques for proving correctness of programs which alter data structures.

Oberuc 245, 249 see predicate calculus Occam's razor 271 London 24-5, 52

INTRODUCTION If let loose, resolution theorem-provers can waste time in many ways. They can continually rearrange the multiplication brackets of an associative multiplication operation or replace terms t by ones like f(f(f(t, e), e), e) where f is a multiplication function and e is its identity. Generally they continually discover and misapply trivial lemmas. Global heuristics using term complexity do not help much and ad hoc devices seem suspicious. On the other hand, one would like to evaluate terms when possible, for example we would want to replace 5 4 by 9. More generally one would like to have liberty to simplify, to factorise and to rearrange terms. The obvious way to deal with an associative multiplication would be to imitate people, and just drop the multiplication brackets. However used or abused the basic facts involved in such manipulations form an equational theory, T, that is, a theory all of whose sentences are universal closures of equations. Under certain conditions, we will be able to build the equational theory into the rules of inference. The resulting method will be resolution-like, the difference being that concepts are defined using provable equality between terms rather than literal identity. Therefore the set of clauses expressing the theory will not be among the input clauses, so no time will be wasted in the misapplication of trivial lemmas, since the rules will not waste time in this way.

The frame problem in representing natural-language information is discussed. It is argued that the problem is not restricted to problem-solving-type situations, in which it has mostly been studied so far, but also has a broader significance. A new solution to the frame problem, which arose within a larger system for representing natural-language information, is described. The basic idea is to extend the predicate calculus notation with a special operator, Unless, with peculiar properties. Some difficulties with Unless are described. THE FRAME PROBLEM This paper proposes a method for handling the frame problem in representing conceptual, or natural-language-type information.

C. COOPER 21 3 Data representation--the key to conceptualisation: D. B. VIGOR 33 MECHANISED MATHEMATICS 45 4 An approach to analytic integration using ordered algebraic expressions: L. I. HODGSON 47 5 Some theorem-proving strategies based on the resolution principle: J. L DARLINGTON 57 MACHINE LEARNING AND HEURISTIC PROGRAMMING 73 6 Automatic description and recognition of board patterns in Go-Moku: A. M. MURRAY and E. W. Etcomc

The formulation of the resolution principle by J. A. Robinson (1965a) has provided the impetus for a number of recent efforts in automatic theoremproving. In particular, the program PG1 (Wos et al. 1964, 1965), written by L. Wos, G. A. Robinson and D. F. Carson for the Control Data 3600, utilises the resolution principle in conjunction with a'unit preference strategy' and a'set of support strategy' to produce efficient proofs in first-order functional logic and group theory. These programs have generated proofs of some interesting propositions of number theory, in addition to theorems of first-order functional logic and group theory. A'literal' is an n-place predicate expression F(xi, x2,.-.., x) or its negation F(xi, x2,., x „) whose arguments are individual variables, individual constants, or functional expressions. Quantifiers do not occur in these formulae, since existentially quantified variables have been replaced by functions of universally quantified ones, and the remaining variables may therefore be taken as universally quantified.

The two outstanding figures in the history of computer science are Alan Turing and John von Neumann, and they shared the view that logic was the key to understanding and automating computation. In particular, it was Turing who gave us in the mid-1930s the fundamental analysis, and the logical definition, of the concept of'computability by machine' and who discovered the surprising and beautiful basic fact that there exist universal machines which by suitable programming can be made to t This essay is an expanded and revised version of one entitled The Role of Logic in Computer Science and Artificial Intelligence, which was completed in January 1992 (and was later published in the Proceedings of the Fifth Generation computer Systems 1992 Conference). Since completing that essay I have had the benefit of extremely helpful discussions on many of the details with Professor Donald Michie and Professor I. J. Good, both of whom knew Turing well during the war years at Bletchley Park. Professor J. A. N. Lee, whose knowledge of the literature and archives of the history of computing is encyclopedic, also provided additional information, some of which is still unpublished. Further light has very recently been shed on the von Neumann side of the story by Norman Macrae's excellent biography John von Neumann (Macrae 1992). Accordingly, it seemed appropriate to undertake a more complete and thorough version of the FGCS'92 essay, focussing somewhat more on the interesting historical and biographical issues. I am grateful to Donald Michie and Stephen Muggleton for inviting me to contribute such a'second edition' to the present volume, and I would also like to thank the Institute for New Computer Technology (ICOT) for kind permission to make use of the FGCS'92 essay in this way. 1 LOGIC, COMPUTERS, TURING, AND VON NEUMANN

EBL systems 117 see also non-deterministic finite see also explanation-based learning automata device malfunction data 165 ECG interpretation 306-7 description length of propositions Eckert, J.P. 4, 11 obtained 164 Eckert-Mauchly computers 11 Diagram Configuration (DC) model, EDSAC computer 11 perceptual chunks used EDVAC computer 11 420

Turing's best known work is concerned with whether universal machines can decide the truth value of arbitrary logic formulae. However, in this paper it is shown that there is a direct evolution in Turing's ideas from his earlier investigations of computability to his later interests in machine intelligence and machine learning. Turing realised that machines which could learn would be able to avoid some of the consequences of Godes and his results on incompleteness and undecidability. Machines which learned could continuously add new axioms to their repertoire. Inspired by a radio talk given by Turing in 1951, Christopher Strachey went on to implement the world's first machine learning program.

The two outstanding figures in the history of computer science are Alan Turing and John von Neumann, and they shared the view that logic was the key to understanding and automating computation. In particular, it was Turing who gave us in the mid-1930s the fundamental analysis, and the logical definition, of the concept of'computability by machine' and who discovered the surprising and beautiful basic fact that there exist universal machines which by suitable programming can be made to t This essay is an expanded and revised version of one entitled The Role of Logic in Computer Science and Artificial Intelligence, which was completed in January 1992 (and was later published in the Proceedings of the Fifth Generation computer Systems 1992 Conference). Since completing that essay I have had the benefit of extremely helpful discussions on many of the details with Professor Donald Michie and Professor I. J. Good, both of whom knew Turing well during the war years at Bletchley Park. Professor J. A. N. Lee, whose knowledge of the literature and archives of the history of computing is encyclopedic, also provided additional information, some of which is still unpublished. Further light has very recently been shed on the von Neumann side of the story by Norman Macrae's excellent biography John von Neumann (Macrae 1992). Accordingly, it seemed appropriate to undertake a more complete and thorough version of the FGCS'92 essay, focussing somewhat more on the interesting historical and biographical issues. I am grateful to Donald Michie and Stephen Muggleton for inviting me to contribute such a'second edition' to the present volume, and I would also like to thank the Institute for New Computer Technology (ICOT) for kind permission to make use of the FGCS'92 essay in this way. 1 LOGIC, COMPUTERS, TURING, AND VON NEUMANN