Programs With Common Sense

PROGRAMS WITH COMMON SENSE
John McCarthy
Computer Science Department
Stanford University
Stanford, CA 94305
jmc@cs.stanford.edu
http://www-formal.stanford.edu/jmc/
1959
1 Introduction
Interesting work is being done in programming computers to solve problems
which require a high degree of intelligence in humans. However, certain
elementary verbal reasoning processes so simple that theycan be carried
out by any non-feeble minded human have yet to be simulated by machine
programs.
This paper will discuss programs to manipulate in a suitable formal lan-
guage (most likely a part of the predicate calculus) common instrumental
statements. The basic program will draw immediate conclusions from a list
of premises. These conclusions will be either declarative or imperative sen-tences. When an imperative sentence is deduced the program takes a cor-
responding action. These actions may include printing sentences, moving
sentences on lists, and reinitiating the basic deduction process on these lists.
Facilities will be provided for communication with humans in the system
via manual intervention and display devices connected to the computer.
The advice taker is aproposed program for solving problems by manip-
ulating sentences in formal languages. The main dierence between it and
1
other programs or proposed programs for manipulating formal languages (the
Logic Theory Machine of Newell, Simon and Shaw and the Geometry Pro-
gram of Gelernter) is that in the previous programs the formal system was
the subject matter but the heuristics were all embodied inthe program. In
this program the procedures will be described as much as possible in the
language itself and, in particular, the heuristics are all so described.
The main advantages we expect the advice taker to have is that its behav-
ior will be improvable merely by making statements to it, telling it about its
symbolic environment and what is wanted from it. To make these statements
willrequire little if any knowledge of the program or the previous knowledge
of the advice taker. One will be able to assume that the advice taker will
have available to it a fairly wide class of immediate logical consequences of
anything it is told and its previous knowledge. This property is expected to
have much in common with what makes us describe certain humans as hav-
ing common sense. Weshall therefore say that a program has common sense
if it automatically deduces for itself a suciently wide class of immediate
consequences of anything it is told and what it already knows.
The design of this system will be a joint project with Marvin Minsky, but
Minsky is not to be held responsible for the views expressed here.1
Before describing the advice taker in any detail, I wouldlike to describe
more fully our motivation for proceeding in this direction. Our ultimate
objective is to make programs that learn from their experience as eectively
as humans do. It may not be realized how far we are presently from this
objective. It is not hard to make machines learn from experience to make
simple changes in their behavior of a kind which has been anticipated by
theprogrammer. For example, Samuel has included in his checker program
facilities for improving the weights the machine assigns to various factors in
evaluating positions. He has also included a scheme whereby the machine
remembers games it has played previously and deviates from its previous
play when it nds a position which it previously lost. Suppose, however, that
we wanted an improvement inbehavior corresponding, say, to the discovery
by the machine of the principle of the opposition in checkers. No present or
presently proposed schemes are capable of discovering phenomena as abstract
as this.
If one wants a machine to be able to discover an abstraction, it seems
most likely that the machine must be able to represent this abstraction in
11996: This was wishful thinking. Minsky's...