We have written a program which will recognize a range of objects including a cup, a wedge, a hammer, a pencil, and a pair of spectacles. A visual image, represented by a 64.x 64 array of light levels, is first partitioned into connected regions. These regions are chosen to have welldefined edges. Having chosen the regions, the program then computes properties of and relations between regions. Properties include shape as defined by Fourier analysis of the s--tfr equation of the bounding curve. A typical relation between regions is the degree of adjacency. Finally, the program matches the actual relational structure of the regions of the picture with ideal relational structures representing various objects, using a heuristic search procedure, and selects that object whose relational structure best matches the actual picture. INTRODUCTION In November 1969, a Mark i robot device (Barrow and Salter 1970) was connected on-line to the ICI, 4130 computer of the Department of Machine Intelligence and Perception, University of Edinburgh.

The Genetics Counselor is a computer program, written in LISP, designed to handle problems of medical genetics counseling. It is an attempt to apply the methods of artificial intelligence research to medical diagnostic problems. The program attempts to map the data space of a family-tree structure into the hypothesis space of classical Mendelian genetics by use of a heuristic search. The input data are the family members along with their children (or parents), and phenotype. The program generates a family tree and searches for consanguinity.

Yet the attention given to the program as an application of artificial intelligence research has tended to obscure the more general concerns of the project investigators.

K.A.PATON 411 24 Centromere finding: some shape descriptors for small chromosome outlines.

Both the analytical philosopher and the designer of intelligent software are doing what might be called'mental engineering': constructing precise, formal models of some aspects of intelligent thought or behaviour. There is a wide gap between them, but it is narrowing.

The solution to this simple problem would then guide the solution of the original problem. Minsky (1961) has discussed complex planning of this'homomorphic model' type, and has stressed the potential reduction in total search effort to be won. In the same paper he has also considered the use of semantic models' as a form of complex planning in a mathematical context. The successful geometry theorem-proving program of Gelernter (1959), which used a diagram' to test the validity of propositions, is a wellknown example of this form of planning. Recently Sandewall (1969) has defined a Planning Problem Solver (P P This is an attempt to explore in detail complex planning of the homomorphic model' type as applied to the

A formal description is given of GT 4, a revised and extended version of the Graph Traverser. Methods are described whereby GT4 can improve its performance at run time (a) by automatic optimization of parameters used by the evaluation function and (b) by dynamic re-ordering of operators. Neither method depends upon there being any successful searches in the program's past experience of a given problem. The essential feasibility of both approaches has been validated in experimental tests using sliding block puzzles. Two planned extensions, 'local smoothing' and'regionalization' are described. INTRODUCTION The Graph Traverser (Doran and Michie 1966), and subsequent work based on it, represents an attempt to adapt game-playing methods, particularly those of Samuel (1959), to automatic problem-solving. The design objective is not the simulation of human problem-solving as a study in psychology, but rather to provide an efficient general-purpose search procedure appropriate to non-numerical problem domains. There is a parallel with the development of direct search techniques for numerical function minimization, for example pattern search (Hooke and Jeeves 1961), simplex (Spendley, Hext and Himsworth 1962, Nelder and Mead 1965).

The equivalence problem for program schemes, or for programs, is reduced to the proving of a theorem in second-order logic. This work extends Manna's first-order logic reductions. Some examples of the technique are given together with a suggested method for obtaining proofs in special cases by firstorder methods. INTRODUCTION Several workers in recent years have considered using techniques and ideas of various mathematical theories of computation for proving interesting results about computer programs. This paper is concerned with two of these approaches.

F(n,$) as introduced here corresponds to A.N.Prior's (1957, 1968) expression Fir.

R.M.BURSTALL 373 23 Assertions: programs written without specifying unnecessary order.