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STANFORD ARTIFICIAL INTELLIGENCE LABORATORY
1974 ARPA Project Summary
Prepared for: ARPA IPTO Principal Investigators Meeting
March 12-14, 1975
Prepared by: John McCarthy
Computer Science Department
Stanford University
Stanford, California 94305
Formal Reasoning -- John McCarthy, Richard Weyhrauch, et al
Using our LCF proof-checker, we have produced an axiomatization of
the programming language PASCAL. This represents a major step toward
using LCF as a practical program verification system.
Newey in his thesis used LCF to prove the partial correctness of the
LISP 1.5 interpreter and began a project to prove the correctness
of a LISP compiler (called LCOM0). This compiler is actually more than
a toy in that it is used in the LISP course here at Stanford. This
thesis as a whole represented a kind of case study which demonstrated
our ability to check the correctness large LISP programs.
Automatic Deduction -- David Luckham, et al
A successful new automatic programming system accepts descriptions of
library routines, programming methods, and program specifications in
a high level semantic definition language. It returns programs
written in a subset of ALGOL that satisfy the given specifications.
Experimental applications include computing arithmetical functions
and planning robot strategies.
Another system works with algorithms expressed in a higher-level
language and automatically chooses an efficient representation for
the data structure. It then produces a program that uses this
representation. Representations considered include certain kinds of
linked-lists, binary trees, and hash tables.
Program Understanding Systems -- Cordell Green, et al
The EXAMPLE program that infers recursive list-processing functions
from example input-output pairs was completed during 1974. This
system demonstrates the possibility of using fairly natural methods
of program specification.
The PUP system was our first to show a rudimentary "program
understanding" behavior. By following a simple chain of reasoning,
it can synthesize a few short programs, such as interchange of
elements, three-element sort, and integer square root.
A system was completed which, given a program expressed in terms of
high-level information structures such as sets, ordered sets, and
relations, automatically chooses efficient implementation-level
representations and produces an equivalent program that uses these
representations.
A very comprehensive dialog was completed which exhibits a knowledge
base of rules for the synthesis of sorting programs. Although not
all the necessary synthesis rules have been codified, it is
reasonably clear how to do so. This work is aimed at the deepest
understanding of a simple program synthesis yet attempted.
Work was completed on a pilot system that interactively synthesizes
what is essentially Winston's concept formation program. This system
points toward the feasibility of systems for writing long,
domain-specific programs.
Natural Language Understanding -- Terry Winograd, et al
A system was completed that links natural language
understanding, inference, and generation of natural language output.
This is the first such system with a strong theoretical basis, namely
Conceptual Dependency.
Work was begun on a knowledge representation language for natural
language systems which combines the advantages of procedural and
declarative formalisms. It will be developed over the next three
years as the basis for several understander projects.
Hand-eye Research -- Tom Binford, Lynn Quam, et al
We have used near and far field stereo vision and motion parallax to
locate objects spatially and to automatically generate contour maps.
We completed design of a manipulation system AL, which combines
a control language with a planning system to aid in extended tasks
such as assembly. AL has new features such as:
ALGOL-like control; interrupts and control monitors; simultaneous
coordinted motion of two or more arms;
and a planning system. The implementation is well
underway. The planning system includes a subsystem for
keeping track of the locus of parts, translating semantic constraints
into mathematical constraints.
We completed assembly of a hinge
using two arms in coordinated non-simultaneous motion.
We have carried out two subassemblies of a two stroke gasoline engine.
We have completed some modules of a visual system
to be used for control of assembly. The system has facilities for
manual generation of 2D symbolic models, matching of curves
in an image with those of the model. The system has the
facility for using 3D models, as in CAD, predicting symbolic 2D
models from 3D.
We have also completed recognition of complex objects
such as a doll and a toy horse
using the spine-cross section representation.
The system forms its own models, and matches in a way suitable for a large
visual memory, by making summary descriptions which it uses to find
a subclass of models similar to the test object.
Training
During the last year, eleven members of our staff published Ph.D.
dissertations and another 32 graduate students received direct
support.