This report describes a system of programs which perform natural

language processing based on an underlying language free

(conceptual) representation of meaning. This system is used to

produce sentence paraphrases which demonstrate a form of

understanding with respect to a given context. Particular emphasis

has been placed on the major subtasks of language analysis (mapping

natural language into conceptual structures) and language generation

(mapping conceptual structures into natural language), and on the

interaction between these processes and a conceptual memory model.

In visual-feedback work often a model of an object and its

approximate location are known and it is only necessary to determine

its location and orientation more accurately. The purpose of the

program described herein is to provide such information for the case

in which the model is an edge or corner. Given a model of a line or

a corner with two or three edges, the program searches a TV window

of arbitrary size looking for one or all corners which match the

model. A model-driven program directs the search. It calls on

another program to find all lines inside the window. Then it looks

at these lines and eliminates lines which cannot match any of the

model lines. It next calls on a program to form vertices and then

checks for a matching vertex. If this simple procedure fails, the

model-driver has two backup procedures. First it works with the

lines that it has and tries to form a matching vertex (corner). If

this fails, it matches parts of the model with vertices and lines

that are present and then takes a careful look in a small region in

which it expects to find a missing line. The program often finds

weak contrast edges in this manner. Lines are found by a global

method after the entire window has been scanned with the Hueckel

edge operator.

We present various heuristic techniques for use in proving the

correctness of computer programs. The techniques are designed to

obtain automatically the "inductive assertions" attached to the loops

of the program which previously required human "understanding" of the

program's approaches: one in which we obtain the inductive assertion

by analyzing predicates which are known to be true at the entrances

and exits of the loop (top-down approach), and another in which we

generate the inductive assertion directly from the statements of the

loop (bottom-up approach).

A program is described which traces around objects in a picture,

using the picture scanner attached to the PDP-1 computer, and fits

curves to the edges.

A program that checks proofs in J. A. Robinson's formulation of

predicate calculus has been programmed in LISP 1.5. The program is

available in CTSS at Project MAC and is also available as a card

deck. The program is used for class exercises at Stanford.

Some comments are made on the characteristics believed desirable in

the next eye for the Stanford Artificial Intelligence Project and a

proposal is given for a program to input scenes using the eye.

This paper is a discussion of several methods for the connection of

a television camera to the PDP-1 computer. Three of these methds

are discussed in detail and have in common that only a 36 bit

portion of any horizontal scanning line may be read and this

information is read directly into the working registers of the

computer. The fourth involves a data channel to read information

directly into the core memory of the computer, and is mentioned only

in passing. The major concepts and some of the details of these

methods are due to Marvin Minsky.