The problem of producing sentences of a transformational grammar by using a random generator to create phrase structure trees for input to the lexical insertion and transformational phases is discussed. A purely random generator will produce base trees which will be blocked by the transformations, and which are frequently too long to be of practical interest. A solution is offered in the form of a computer program which allows the user to constrain and direct the generation by the simple but powerful device of restricted subtrees. The program is a directed random generator which accepts as input a subtree with restrictions and produces around it a tree which satisfies the restrictions and is ready for the next phase of the grammar. The underlying linguistic model is that of Noam Chomsky, as presented in Aspects of the Theory of Syntax.

This paper is a survey and discussion of research work relevant to the task of constructing some kind of reasoning robot. The emphasis is entirely on the organization of the reasoning processes, in particular planning, rather than on hardware. In practice the reasoning would most probably be carried out within a digital computer. My objective is to clarify the relationship between some superficially rather disparate approaches to this task, and simultaneously to indicate what seem to be the key problem areas. No new experimental results are presented, but the approach to the subject which I have adopted is a consequence of earlier experimentation with a simple computer simulation of a robot (Doran 1968a, 1969).

A minimal:robot,Icnown as Freddy, has been constructed with the aim of connecting a usable device online to the Department's lc L 4130, under the Multi-Pop time-sharing system, and discovering the snags. (See figure 1). Various technical problems arise when such a device runs free. It is much easier to anchor it and allow it to push its world about. Our present world is a three-foot diameter sandwich of hardboard and polystyrene which is light and rigid.

Computer Science Department, Stanford University (1969). Ph.D. dissertation

Machine Intelligence 5. B. Meltzer & D. Michie (eds.), 78-98. Edinburgh: Edinburgh University Press.

A computer program capable of acting intelligently in the world must have a general representation of the world in terms of which its inputs are interpreted. Designing such a program requires commitments about what knowledge is and how it is obtained. Thus, some of the major traditional problems of philosophy arise in artificial intelligence. More specifically, we want a computer program that decides what to do by inferring in a formal language that a certain strategy will achieve its assigned goal. This requires formalizing concepts of causality, ability, and knowledge. Such formalisms are also considered in philosophical logic. The first part of the paper begins with a philosophical point of view that seems to arise naturally once we take seriously the idea of actually making an intelligent machine.

It seems most unlikely that one could in general write purely applicative Schonfmkel descriptions', like (5), of functions already known to one in some other form. Fortunately there is a general procedure -- the Schonfmkel procedure -- which, when applied to any expression written in the more intuitive lambda-calculus notation, will produce a correct translation of it into the Schonfinkel notation.

A question-answering system. Tech. Note 15, AI Group, Stanford Research Institute, Menlo Park, Calif.

Institut Blaise Pascal, C.N.R.S., 23, Rue du Maroc, 75, Paris XIX, France We study some aspects of a general game-playing program. Such a program receives as data the rules of a game: an algorithm enumerating the moves and an algorithm indicating how to win. The program associates to each move the conditions necessary for this move to occur. It must find how to avoid a dangerous move. We describe the part of the program playing the combinatorial game in order to win: how it can find the moves which lead to victory and what are the only opponent's moves with which he does not lose. This program has been tried with various games: chess, tictac-too, etc. 1. INTRODUCTION My aim was to realize a program playing several games. The rules of the particular game which it must play are given as data. If we want to have a performing program, it must be capable of studying these rules.

In Meltzer, Bernard and Donald Michie (Eds.). Machine Intelligence 5, pp. 78-98. Edinburgh University Press.