Here is the essence of the frame theory: When one 
encounters a new situation (or makes a substantial change tn 
one's view of a problem), one selects from memory a 
structure called a frame. This is a remembered framework to 
be adapted to fit reality by changing details as necessary. 
A frame is a data-structure for representing a 
stereotyped situation like being in a certain kind of living 
room or going to a child's birthday party. Attached to each 
frame are several kinds of information. Some of this 
information is about how to use the frame. Some is about 
what one can expect to happen next. Some is about what to 
do if these expectations are not confirmed. 
We can think of a frame as a network of nodes 
and relations. The "top levels" of a frame ere fixed, and 
represent things that are always true about the supposed 
situation. The lower levels have many terminals -- "slots" 
that must be filled by specific instances or data. Each 
terminal can specify conditions its assignments must meet. 
(The assignments themselves are usually smaller "sub- 
frames.") Simple conditions are specified by markers that 
might require a terminal assignment to be a person, an object 
of sufficient value, or a pointer to a sub-frame of a certain 
type. More complex conditions can specify relations among 
the things assigned to several terminals. 
Collections of related frames are linked together 
into frame-systems. The effects of important actions ere 
mirrored by transformations between the framesof a system. 
These are used to make certain kinds of calculations 
economical, to represent changes of emphasis and attention, 
and to account for the effectiveness of "imagery." 
For visual scene analysis, the different frames of a 
system describe the scene from different viewpoints, and the 
transformations between one frame and another represent 
the effects of moving from place to place. For non-visual 
kinds of frames, the differences between the frames of a 
system can represent actions, cause-effect relations, or 
changes in conceptual viewpoint. Different frames of a 
system share th._~e same terminals; this is the critical point 
that makes it possible to coordinate information gathered 
from different viewpoints. 
Much of the phenomenological power of the theory 
hinges on the inclusion of expectations and other kinds of 
presumptions. A frame's terminals are normally already filled 
with "default" assignments. Thus'~ frame may contain a 
great many details whose supposition is not specifically 
warranted by the situation. These have many uses in 
representing general information, most likely cases, 
techniques for by-passing "logic," and ways to make useful 
generalizations. 
The default assignments are attached loosely to 
their terminals, so that they can be easily displaced by new 
items that fit better the current situation. They thus can 
serve also as =variables" or as special cases for "reasoning 
by example," or as "textbook cases," and often make the use 
of logical quantifiers unnecessary. 
The frame-systems are linked, in turn, by an 
information retrieval network. When a proposed frame 
cannot be made to fit reality -- when we cannot find terminal 
assignments that suitably match its terminal marker conditions 
-- this network provides a replac:ement frame. These inter- 
frame structures make possible other ways to represent 
knowledge about facts, analogies, and other information useful 
in understanding. 
Once a frame is proposed to represent a situation, 
a matching process tries to assign values to each frame's 
terminals, consistent with the markers at each place. The 
matching process is partly controlled by information 
associated with the frame (which includes information about 
how to deal with surprises) and partly by knowledge about 
the system's current goals. There are important uses for the 
information, obtained when a matching process fails; it can be 
used to select an alternative frame that better suits the 
situation. 
LOCAL ~1~1~ ~LOS~L T1~EOK~E~ FO~ Vt~I01~ 
When we enter a room we seem to see the entire 
scene at a glance. But seeing is really an extended process. 
It takes time to fill in details, collect evidence, make 
conjectures, test, deduce, and interpret in ways that depend 
on our knowledge, expectations and goals. Wrong first 
impressions have to be revised. Nevertheless, all this 
proceeds so quickly and smoothly that it seems to demand a 
special explanation. 
Would parallel processing help? This is a more 
technical question than it might seem. At the level of 
detecting elementary visual features, texture elements, 
stereoscopic and motion-parallax cues, it is obvious that 
parallel processing might be useful. At the level of IFouping 
features into objects, it is harder to see exactly how to use 
parallelism, but one can at least conceive of the aggregation 
of connected "nuclei" (Guzman TR-228), or the application of 
boundary line constraint semantics (Waltz TR-271), 
performed in a special parallel network. 
At "higher" levels of cognitive processing, 
however, one suspects fundamental limitations in the 
usefulness of parsllelism. Many "integral" schemes were 
proposed in the literature on "pattern recognition" for 
parallel operations on pictorial material --perceptrons, 
integral transforms, skeletonizers, and so forth. These 
mathematically and computationally interesting schemes might 
quite possibly serve as ingredients of perceptual processing 
theories. But as ingredients only\] Bas!celly, "integral" 
methods work only on*isolated figures in two dimensions. 
They fail disastrously in coping with complicated, three- 
dimensional scenery. 
The new, more successful symbolic theories use 
hypothesis formation and confirmation methods that seem, on 
the surface at least, more inherently serial. It is hard t_oo 
solve any very complicated problem without L, ivinl¢ essentially 
full attention s at different times, to different sub-problems. 
Fortunately, however, beyond the brute idea of doing many 
things in parallel, one c'an imagine a more serial process that 
deals with large, complex, symbolic structures as units! Thia 
opens a new theoretical "niche" for .performing a rapid 
selection of large substructures; in this niche our theory 
hopes to find the secret of speed, both in vision and in 
ordinary thinking. 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
~EEtl16 i~ C'JB£ 
Inthe tradition of Guzman and Winston, we assume 
that the result of looking at a cube is a structure something 
like that in figure 1..The substructures "A" and "B" 
represent details or decorations on two faces of the cube. 
Whenwe move to the right, face "A" disappears from view, 
while the new face decorated with "C" is now seer If we 
had to analyse the scene from the start, we would have to 
I (l) lose the knowledge about "A," 
(2) recompute B, and 
(3) compute the description of "C.* 
cube 
~XI\ I 
~,--~ left-above-~.~(~ - 
I I 1 I parallelogram ~....~L~ ,~ 
,"--- i 0 > etc. 
A B 
I But since we know we moved to the right, we can save "B" 
by assigning it also to the "left face" termlnII of a second I 
cube-frame. To save "A (just in cased we connect it also 
to an extra, invisible face-terminal of the niw cube-scheme 
as in figure Z 
i /~invisible 
,. 
d I 
A E B C i 
If later we,move back to the left, 
we can reconstruct the first scene without any perceptual 
computation at all: 
! . just restore the top-level pointers to the first cube-frame. 
We now need a place to store ~"; we Can eK:ld yet another 
invisible face to the right in the first cube-framel See filNre I 3. 
We could extend this to represent further excursions 
" M°ve-Right ~ C~ 
transformation ~/l~ 
I % / 
__ "II P.._hl IA pl 
I 
ft~ VKE 3 
--"left-vertical parallelogram" ht-vertical parallelogram" 
square" (in space) 
tO5" 
I 
I 
around the object. This would lead to a more comprehensive B 
frame system, in which each frame represents a different 
"perspective" of a cube. In figure 4 there ere three frames 
~RIGH_~T ~RIGHT _~~ Spatial Frames Ii 
B _ left - C) 
left FIC~U~E ~. 
corresponding to 45-degree MOVE-RIGHT and MOVE-LEFT 
actions. If we pursue this analysis, the resulting system can 
become very large; more complex objects need even more 
different projections. It is not obvious either that all of them 
are normally necessary or that just one of each variety is 
adequate. It all depends. 
It is not proposed that this kind of complicated 
structure is recreated every time one examines an object. It 
is imagined instead that a great collection of frame systems is 
stored in permanent memory, and one of them is evoked 
when evidence and expectation make it plausible that the 
scene in view will fit It. How are they acquired? We 
propose that if a chosen frame does not fit well enough, end 
if no better one is easily found, and if the matter Is important 
enough, then an adaptation of the best one so far discovered 
will be constructed and remembered for future use. 
Each frame has terminals for attaching pointers to 
substructures. Different frames can share the same terminal, 
which can thus correspond to the same physical feature as 
seen in different views. This permits us to represent~ in a 
single place, view-independent information gathered st 
different times and places. This is important also in non- 
visual applications. 
The matching.process which decides whether a 
proposed frame is suitable is controlled partly by one's 
current goals and partly by information attached to the frame! 
the frames carry terminal markers and other constraints, 
while the goals are used to decide which of these constraints 
are currently relevantL Generally, the matching process could 
have these components: 
Pictorial Frames I 
Relation Markers in common-terminal structure can represent more invar- 
iant (e.g. three-dimensional) properties. 
I 
I 
(l) A frame, once evoked on the basis of partial evidence 
or expectat!on, would first direct a test to confirm 
its own appropriateness , using knowledge about 
recently noticed features, loci, relations, and 
plausible Sub-frames. The current goal list is used 
to decide which terminals and conditions must be 
made to match reality. 
(2) Next it would request information needed to assign 
values to those terminals that cannot retain their 
default assignments. For example, it might request 
a description of face "C," if this terminal is 
currently unassigned, but only if it is not marked 
"invisible." Such assignments must avee with the 
current markers at the terminal. Thus, face "C" 
might already~have markers for such constraints or 
expectations as: 
I 
I 
I 
I 
I 
, Right-middle visual field. 
, Must be assigned. 
, Should be visible; if not, consider 
moving right. 
. , Should be a cube-face sub-frame. 
* Share left vertical boundary 
terminal with face "B." 
* If failure, consider box-lying-on-side 
frame. 
* Same backip'ound color as face "B." 
(3) Finally, if informed about a transformation (e.g., an 
impending motion) it would transfer control to the 
appropriate other frame of that system 
Within the details of the control scheme are opportunities to 
embed many kinds of knowledge. When a terminol-essilpdng 
attempt fails, the resulting error message can be used to 
propose a second-guess alternative. Later it is shown how 
memory can be organized into a "Similarity Network" as 
proposed in Winston's thesis (TR-23|). 
I 
I 
I 
I 
i 
I 
lOI= I 
i 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I 
I@ VI@I@}l ~YIII\]3OhIC? 
Can one really believe that a person's appreciation 
of three-dimensional structure can be so fragmentary and 
atomic as to be representable in terms of the relations 
between parts of two-dimensional views? Let us separate, 
at once, the two issues: is imagery symbolic? and is it based 
on two-dimensional fragments? The first problem is one of 
degree; sure!y everyone would agree that at some level 
vision is essentially symbolic. The quarrel would be between 
certain naive conceptions on one side -- in which one accepts 
seeing either as picture-like or as evoking imaginary solids -- 
against the confrontation of such experimental results of 
Piaget (1956) and others in which many limitations that one 
might fear wou!d result from symbolicrepresentations ere 
shown actually to exist! 
As for our second question: 
the issue of two-vs, three-dimensions evaporates at the 
symbolic evel. 
The very concept of dimension becomes inappropriate. Each 
type of symbolic representation of an object serves some 
goals well and others poorly. If we attach the relation labels 
left-of~ right-o_~f and abo~'e between parts of the structure, 
Say, as markers on pairs of terminals, certain manipulations • 
will work out smoothly; for example, some properties of 
these relations are "invariant" if we rotate the cube while 
keeping the same face on the table. Most objects have 
"permanent" tops and bottoms. But if we turn the cube on 
its side such predictions become harder to make; people 
• have great difficulty keeping track of the faces of a six- 
colored cube if one makes them roll it around in their mind. 
If one uses instead more "intrinsic" relations like 
next-to and opposite-t_o,o then turning the object on its side 
disturbs the "image" much less. In Winston's thesis we see 
how systematic replacements (e.g., of *left" for "behind," end 
"right" for "in-front-of") can deal with the effect of spatial 
rotation. 
Visual experience seems continuous. One reason 
is that we move continuously. A deeper explanation is that 
our "expectations". usually interact smoothly with our 
perceptions. Suppose you were to leave a room, close the 
door, turn to reopen it, and find an entirely different room. 
You would be shocked, The sense of change would be hardly 
less striking if the world suddenly changed before your eyes. 
A naive theory of phenomenological continuity is that we see 
so quickly that our image changes as fast as'does the scene. 
There is an alternative theory: the changes in one's frame- 
structure representation proceed at their own pace; the 
system prefers to make small changes whenever possible; 
and the•illusion of continuity is due to the persistence of 
assignments to terminals common to th__ee different view- 
frames. Thus, continuity depends on the confirmation of 
expectations which in turn depends on rapid access to 
remembered knowledge about the visual world. 
Just before you enter a room, you usually know 
enough to "expect" a room rather than, say, • landscape. You 
can •usually tell just by the character of the door. And you 
can often select in advance a frame for the new room. Very 
often, one expects a certain particular room. Then many 
assignments are already filled in, 
Io'/ 
The simplest sort of room-frame candidate is like 
the inside of a box. Following our cube-model, the room- 
frame might have the top-level structure shown in figure 5. 
~~a, ceiling / a c 
I 
left wall g center wall lh right wall 
! 
• "'• 
fl oor 
FIGUR*" 5" 
One has to •assign to the frame's terminals the 
things that are seen. If the room is familiar, some are already 
assigned. If no expectations are recorded already, the first 
priority might be Iocalcing the principal geometric landmarks. 
To fill in LEFT WALL one might first try to find edges "a" end 
"d" and then the associated corners "ag" and "gd." Edge "g," 
for example, is usually easy to find because it should 
intersect any eye-level horizontal scan from left to right. 
Eventually, "ag," "gb," and "ba" must not be too inconsistent 
with one another -- because they are the same physical 
vertex. 
However the process is directed, there are some 
generally useful knowledge-based tactics. It is probably 
easier to find edge "e '~ than any other edge, because if we 
have just entered a normal rectangular room, then we may 
expect that 
* Edge "e" is a horizontal line. 
* R is below eye level. 
* It defines a floor-wall texture 
boundary. 
Given an expectation about the size of • room, we can 
estimate the elevation of "e,= and vice verse. In outdoor 
scenes, "e" is the horizon and on flat round we can expect 
to see it at eye-level. If we fail quickly to locate and essiin 
this horizon, we must consider rejecting the proposed frame: 
either the room is not normal or there is a large obstruction. 
The room-analysis strategy might try next to 
establish some other landmarks. Given "e,= we next look for 
its left and right corners, and then for the verticals rising 
from them. Once such gross geometrical landmarks ere 
located, we can guess the room's general shape end size. 
This might lead to selecting a new frame better matched to 
that shape and size, with additional markers confirming the 
choice and completing the structure with further details. 
If the new room is unfamiliar, no pre-assembled 
frame can supply fine details; more scene-analysis is needed. 
Even so, the complexity of the work can be reduced, given 
suitable subframes for constructing hypotheses about 
substructures in the scene. How useful these will be 
depends both on their inherent adequacy and on the quality 
of the expectation process that selects which one to use 
next. One can say a lot even about an unfamiliar roont Most 
rooms are like boxes, and they can be categorized into types" 
kitchen, hall, living room, theater, and so on. One knows 
dozens of kinds of rooms and hundreds of particular rooms; 
one no doubt has them structured into some sort of similarity 
network for effective access. This will be discussed later. 
A typical room-frame has three or four visible 
walls, each perhaps of a different "kind." One knows many 
kinds of walls: walls with windows, shelves, pictures, and 
fireplaces. Each kind of room has its own kinds of walls. A 
typical wall might have a 3 x 3 array of region-terminals 
(left-center-right) x (top-middle-bottom) so that wall-objects 
Can be assigned qualitat!ve locations. One would further 
want to locate objects relative to geometric inter-relations in 
order to represent such facts as "Y is a little above the 
center of the line between X and Z." 
In three dimensions, the location of a visual feature 
of a subframe is ambiguous, given only eye direction. A 
feature in the middle of the visual field could belong either to 
a Center Front Wall object or to a High Middle Floor object; 
these attach to different subframes. The decision could 
depend on reasoned evidence for support, on more directly 
visual distance information derived from stereo disparity or 
motion-parallax, or on plausibility information derived from 
other frames: a clock would be plausible only on the wall- 
frame while a person is almost certainly standing on the floor. 
Given a box-shaped room, lateral motions induce 
orderly changes in the quadrilateral shapes of the walls as in 
figure 6. A picture-frame rectangle, lying flat against a wall, 
MOVE RIGHT 
=,,uu,u transform in the same way a,J does its wall. If a 
"center-rectangle" is drawn on a left wall it will appear to 
project out because one makes the default assumption that 
any such quadrilateral is actually a rectangle hence must lie 
in a plane that would so project. In figure 7A, both 
quadrilaterals could "look like" rectangh.s, but the one to the 
right does not match the markers for a "left rectangle" 
subframe (these require, e.g.,, that the left side be longer 
than the right side). That rectangle is therefore represented 
by a center-rectangle frame, and seems to project out as 
though parallel to the center wall. 
Thus we must not simply assign the .label 
"rectangle" to a quadrilateral but to a particular frame of a 
rectangle-system. When we move, we expect"w--hatever 
space-transformation is applied to the top-level system will 
be applied also to its subsystems as suggested in figure 7B. 
Similarly the sequence of elliptical projections of a 
circle contains congruent pairs that are visually ambiguous as 
shown in figure 8. But because wall objects usually lie flat, 
we assume that an ellipse on a left wall is a left-ellipse, 
expect it to .transform the same way as the left wall, and are 
• not surprised if the prediction is confirmed. 
FIC~URE" Io 
I 
I 
! 
I,, 
I 
I 
! 
I *~.~._ I. 7A 
| 
right-side r 
O()O ! 
! 
! 
I00 0 001 I F~u~E 9 
DEF~ILT ~\]6R~I~RT 
I 
I 
I 
I 
I 
I 
I 
While both Seeing and Imagining result in 
assignments to frame terminals, Imagination leaves us •wider 
choices of detail and variety of such assignments. Frames 
are probably never stored in long-term memory with 
unassigned \[erminal values. Instead, what really happens is 
that frames are stored with weakly-bound default 
assignments at every terminalt These manifest themselves as 
often-useful but sometimes counter-productive stereotypes. 
Thus in the sentence "John kicked the ball," you 
probably cannot think of a purely abstract ball, but must 
imagine characteristics of a vaguely particular ball; it 
probably has a certain default size, default color, default 
weight. Perhaps it is a descendant of one you first owned or 
were injured by. Perhaps it resembles your latest one. In 
any case your image lacks the sharpness of presence 
because the processes that inspect and operate upon the 
weakly-bound default features are very likely to change, 
adapt, or detach them. • 
WOBI)B, BE~'ITE~CE~ ~l:ll) II~ERI:IIRfi~ 
The concepts of frame and default assignment 
seem helpful in discussing the phenomenology of "meaning." 
Chomsky (1957) points out that such a sentence as 
I 
(A) "colorless green ideas sleep furiously" 
is treated very differently than the non-sentence 
(B) "furiously sleep ideas green colorless" 
and suggests that because both are "equally nonsensical," 
what is involved in the recognition of sentences must be 
quite different from what is involved in the appreciation ef 
meanings. 
There is no doubt that there are processes 
especially concerned with grammar. Since the meaning of an 
utterance is "encoded" as much in the positional and 
structural relations between the words as in the word 
choices themselves, there must be processes concerned with 
analysing those relations in the course of building the 
structures that will more directly represent the meaning. 
What makes the words of (A) more effective and predictable 
than (B)in producing such a structure -- putting aside the 
question of whether that structure should be called semantic 
or syntactic -- is that the word-order relations in (A) exploit 
the (grammatical) convention and rules people usually use to 
induce others to make assignments to terminals of structures. 
This is entirely consistent with grammar theories. A 
generative grammar.would be a summary description of the 
exterior appearance of those frame rules -- or their 
associated processes -- while the operators of 
transformational grammars seem similar enough to some of 
our frame transformations. 
We certainly cannot assume that "logical" 
meaninglessness has a precise psychological counterpart. 
Sentence (A) can certainly generate an image! The dominant 
frame is perhaps .that of someone sleeping; the default 
system assigns a particular bed, and in it lies a mummy-like 
shape-frame with a translucent green color property. In this 
frame there is a terminal for the character of the sleep -- 
restless, perhaps -- and "furiously" seems somewhat 
inappropriate at that terminal, perhaps because the terminal 
does not like to accept anything so "intentional" for a sleeper. 
"Idea" is even more disturbing , because one expects e 
person, or at least something animate. One senses frustrated 
procedures trying to resolve these tensions and conflicts 
more properly, here or there, into the sleeping framework 
that has been evoked: 
Io9 
i 
Utterance (B) does not get nearly so far because 
no subframeaccepts any substantial fragment. As a result no 
larger frame finds anything to match its terminals, hence 
finally, no top level "meaning" or "sentence" frame can 
organize the utterance as either meaningful or grammatical. 
By combining this "soft" theory with gradations of assignment 
tolerances, one could develop systems that degrade properly 
for sentences with "poor" grammar rather than none~ if the 
smaller fragments -- phrases and sub-clauses,-- satisfy 
subframes well enough, an image adequate for certain kinds 
of comprehension could be constructed anyway, even though 
some parts of the top level structure are not entirely 
satisfied, Thus, we arrive at a qualitative theory of 
"grammatical:" 
if the top levels are satisfied but some lower terminals are 
not we have a meaningless sentence; if the top is weak but 
the bottom solid, we can have an ungrammatical but 
meaningful utterance. 
I)t~COBI~E 
Linguistic activity involves larger structures than 
can be described in terms of sentential ip'ammar, and these 
larger structures further blur the distinctness of the wntex- 
semantic dichotomy. Consider the following fable, as told by 
W. Chafe ( ! 972): 
There was once a Wolf who saw a Lamb 
drinking at a river and wanted an 
excuse to eat it. For that purpose, 
even though he himself was upstream, 
he accused the Lamb of stirring up the 
water and keeping him from drinkln¢.. 
To understand this, one must realize that the Wolf is lyingt 
To understand the key conjunctive "even though" one must 
realize that contamination never flows upstream. This in turn 
requires us to understand (among other things) the word 
"upstream" itself. Within a declarative, predicate-based 
"logical" system, one might try to formalize "upstream" by 
some formula like: 
\[A upstream B\] 
AND 
\[Event T, Stream muddy at A\] 
= => 
\[Exists \[Event U, Stream muddy at B\]\] 
AND \[Later U, T\] 
t~O 
FJC--URE q 
E 
~-~ . ~S~ 
next-to ~~--__~~ 
Butan adequate definition would need a good deal more. 
What about the fact that the order of things being 
transported by water currents is not ordinarily changed?. A 
logician might try to deduce this from a suitably intricate set 
of '"local" axioms, together with appropriate "induction" 
axioms. I propose instead to represent this knowledge in a 
structure that automatically translocates Spatial descriptions 
from the terminals of one frame to those of another frame of 
the same system. While this might be considered to be a 
form of logic, it uses some of the same mechanisms designed 
for spatial thinking. 
In many instances we would handle a change over 
time, or a cause-effect relation, in the same way as we deal 
with a change in position. Thus, the concept r!ver-flow could 
evoke a frame-system structure something like the following, 
where S\], $2, and S3are abstract slices of the flowing river 
shown in figure 9. 
There are many more nuances to fill in. What is 
"stirring up" and why would it keep the wolf from drinking? 
One might normally assign default floating objects to the S's, 
but here $3 interacts with "stirring up" to yield something 
that "drink" does not find acceptable. Was it "deduced" that 
stirring river-water means that $3 in the first frame should 
have "mud" assigned to it; or is this simply the default 
assignment for stirred water? 
Almost any event, action, change, flow of material, 
or even flow of information can be represented to a first 
approximation by a.two-frame generalized event. The 
frame-system can have slots for agents, tools, side-effects, 
preconditions, generalized trajectories, just as in the "trans" 
verbs of "case grammar" theories, but we have the additional 
flexibility of representing changes explicitly. To see if one. 
has understood an event or action, one can try to build an 
appropriate instantiated frame-Pair. 
I 
I 
I 
I 
I 
I 
i 
I 
l 
I 
I 
i 
i 
I 
I 
I 
I 
l 
I 
! 
! 
t 
I 
I 
I 
I 
I 
I 
t 
I 
I 
I , 
| 
I 
I 
I 
l 
i 
However, in representing changes by simple 
"before-after" frame-pairs, we can expect to pay a price. 
Pointing to a pair is not the same as describing their 
differences. This makes it less convenient to do planning or 
abstract reasoning; there is no explicit place to attach 
information about the transformation. As a second 
approximation, we could label pairs of nodes that point to 
corresponding terminals, obtaining a structure like the 
"comparison-notes" in Winston (TR-23\]), or we might place 
at the top of the frame-system information describing the 
differences more abstractly. Something of this sort will be 
needed eventually. 
~CE~510~ 
We condense and conventionalize, in language and 
thought, complex situations and sequences into compact 
words and symbols. Some words can perhaps be "defined" in 
elegant, simple structures, but only a small part of the 
meaning of "trade" is captured by: 
first frame 
A has × B has Y 
second frame 
B has X • A has Y 
Trading normally occurs in a social context of law, trust and 
convention. Unless we also represent these other facts, most 
trade transactions will be almost meaningless. It is usually 
essential to know that each party usually wants both things 
but has to compromise. It is a happy but unusual 
circumstance in which each trader is glad to get rid of what 
he has. To represent trading strategies, one could insert the 
basic maneuvers right into the above frame-pair scenario: in 
order for A to make B want X more (or want Y less) we 
expect him to select one of the familiar tactics: 
Offer more for Y. 
Explain why X is so good. 
Create favorable side-effect of B having 
I~sparage'the competition. 
Make B think C wants X. 
These only scratch, the surface. Trades usually occur within a 
• scenario tied together by more than a simple chain of events 
each linked to the next. No single such scenario will do; 
when a clue about trading appears it is essential to guess 
which of the different available scenarios is most tikely to be 
useful. 
Charniak's thesis (TR-266) studies questions about 
transactions that seem easy for people to comprehend yet 
obviously need rich default structures. We find in 
elementary school reading books such stories aS: 
Jane was invited to Jack's Birthday Party. 
She wonderedif he would like a kite. 
She went to her room and shook her piggy 
bank. 
It made no sound. 
We first hear that Jane is invited to Jack's 
Birthday Party. Without the party scenario, or at least an 
invitation scenario, the second line seems rather mysterious: 
She wondered if he would like a kite. 
To explain one's rapid comprehension ofthis, we make a 
somewhat radical proposal: 
to represent explicitly, in the frame for a scenario structure, 
pointers to a collection of the most serious problems and 
questions commonly associated with it. 
In fact we shall consider the idea that the frame terminals are 
exactly those questions. 
Thus, for the birthday party: 
Y must get P for X ........ Choose P! 
X must like P ........ - .... Will X likeP? 
Buy P -:- ............ --- Where to buy P? 
Get money to buy P .... Where to get money? 
(Sub-questions of the "present" frame?) 
Y must dress up What should Y wear? 
Certainly these are one's first concerns when one is invited 
to a partY.Th e 'reader is free to wonder • whether this solution 
is acceptable. The question "Will X like P?" certainly matches 
"She wondered if he would like a kite?" and correctly assigns 
the kite to P. But is:our world regular enough that such 
question sets could be pro-compiled to make this mechanism 
often work smoothly? The answer is mixed. We do indeed 
• expect many such questions; we surely do not expect all o! 
them. But surely "expertise" consists partly in not having to 
realize, a._bb i nitio, what are the outstanding problems and 
interactions insituations. Notice, for example, that there is 
no default assignment for the Present in our party-scenario 
fr-ame. This mandates attention to that assignment problem 
and prepares us for a Possible thematic concern. In any case, 
we probably need a more active mechanism for understanding 
"wondered" which can apply the information currently in the 
frame to produce an expectation of what Jane will think 
about. 
The key words and ideas of a discourse evoke substantial 
thematic or scenario structures, drawn from memory with rich 
default assumptions. In any event, the individual statements of a 
• discourse lead to temporary representations -- which seem 
to correspond to what contemporary linguists call "deep 
structures" -- which are then quickly rearranged or 
consumed in elaborating the growing scenario representation. 
In order of "scale," among the ingredients of such a structure 
there might be these kinds of levels: 
EXCU~E~ 
We can think of a frame as describing an "ideal." 
If an ideal does not match reality because it is "basically" 
wrong, it must be replaced. 
But it is in the nature of'ideals.that they are really elegant 
simplifications; their attractiveness derives from their 
simplicity, but their real power depends upon additional 
knowledge about interactions between them! Accordingly we 
need not abandon an ideal because of a failure to instantiate 
it, provided one can explain the discrepancy in terms of such 
an interaction. Here are some examples in which such an 
"excuse" can save a failing match: 
OCCLUSION: A table, in a certain view, should have four legs, 
but a chair might occlude one of them One can look 
for things like T-joints and shadows to support such an 
excuse. 
FUNCTIONAL VARIANT: A chair-leg is usually a stick, 
geometrically; but more important, it is functionally a 
support. Therefore, a strong center post, with an 
adequate base plate, should be an acceptable 
replacement for all the legs. Many objects are multiple 
purpose and need functional rather than physical 
descriptions. 
BROKEN: A visually missing component could be explained as 
in fact physically missing, or it could be broken. 
Reality has a variety of ways to frustrate ideals. 
PARASITIC CONTEXTS: An object that is just like a chair, 
except in size, could be (and probably is) a toy chair. 
The complaint "too small" could often be so interpreted 
in contexts with other things too small, children playing, 
peculiarly large "grain," and so forth. 
In most of those examples, the kinds of knowledge to make 
the repair -- and thus salvage the current frame -- are 
"general" enough usually to be attached to the thematic 
context of a superior frame. 
In moving about a familiar house, we already know 
a dependable structure for "information retrieval" of room 
frames. When we move through Door D, in Room X, we 
expect to enter Room Y (assuming D I.s not the Exit). We 
could represent this as an action transformation of the 
simplest kind, consisting of pointers between pairs of room 
frames of a particular house system. 
When the house is not familiar, a "!ogical" strategy 
might be to move up a level of classification: when you 
leave one room, you may not know which room you are 
entering, but you usually know that it is some room. Thus, 
one can partially evade lack of specific information by dealing 
with classes -- and one has to use some form of abstraction 
or generalization to escape the dilemma of Bartlett's 
commander. 
It?... 
Winston's thesis (TR-23\]) proposes a way to 
construct a retrieval system that cart represent classes but 
has additional flexibility. His retrieval pointers can be made 
to represent goal requirements and action effects as well as 
class memberships. 
What does it mean to expect a chair? Typically, 
four legs, some assortment of rungs, a level seat, 
an upper back. One expects also certain relations 
between these "parts." The legs must be below 
the seat, the back above. The legs must be 
supported by the floo'r. The seat must be 
horizontal, the back vertical, and so forth. 
Now suppose that this description does not match; 
the vision system finds four legs, a level plane, but 
no back. The "difference" between what we 
expect and what we see is "too few backs." This 
suggests not a chair, but a table or a bench. 
Winston proposes pointers from each description 
in memory to other descriptions, with each pointer labelled 
by a difference marker. Complaints about mismatch are 
matched to the difference pointers leaving the frame and thus 
may propose a better candidate frame. Winston calls the 
resulting structure a Similarity Network. 
Is a Similarity Network practical? At first sight, 
there might seem to be a danger of unconstrained growth of 
memory. If there are N frames, and K kinds of differences, 
then there could be as many as K*N*N interframe pointers. 
One might fear that: 
(\]) If N is large, say 10, then N*N is very large -- 
of the order of 10 -- which might be 
impractical, at least for human memory. 
(2) There might be so many pointers for a given 
difference and a given frame that the 
system will not be selective enough to be 
useful. 
(3) K itself might be very large if the system is 
sensitive to many different kinds of issues. 
But, according to contemporary opinions (admittedly, not very 
conclusive) about the rate of storage into human long-term 
memory there are probably not enough seconds in a lifetime 
to cause a saturation problem. 
So the real problem, paradoxically, is that there 
will be too few connections! One cannot expect to have 
enough time to fill out the network to saturation Given two 
frames that should be linked by a difference, we cannot count 
on that pointer being there; the problem may not have 
occurred before. However, in the next section we see how 
to partially escape this p~oblem. 
I 
! 
! 
I 
i 
t 
t 
I 
| 
t 
| 
| 
i 
| 
I 
I 
I 
| 
! 
I 
! 
I 
t 
I 
i 
I 
I 
I 
I 
I 
I 
t 
I 
I 
I 
I 
Surface Syntactic Frames --- Mainly verb and noun 
structures.. 
Prepositional and word-order indicator 
conventions. 
Surface Semantic Frames ---Action-centered 
• meanings of words. 
Qualifiers and relations concerning 
participants, instruments, trajectories and 
strategies, goals, consequences and side- 
effects. 
Thematic Frames --- Scenarios concerned with 
topics, activities, portraits, setting. 
Outstanding •problems and strategies 
commonly connected with topics. 
Narrative Frames --- Skeleton forms for typical 
stories, explanations, and arguments. 
Conventions about loci, protagonists, plot 
forms, development, etc., designed to help a 
listener construct.a new, inatantieted 
Thematic Frame in his own mind. 
5EO~EgTg TO ~EtIIOST 
We can now imagine the memory system as driven 
by two complementary needs. 
On one side are items demanding to be properly represented 
by being embedded into larger frames; on the other side are 
incompletely-filled frames demanding terminal assignments. 
The rest of the system will try to placate these lobbyists, 
but not so much in accord with "general principles" as in 
accord with special knowledge and conditions imposed by the 
currently active goals. 
When a •frame encounters trouble -- when an 
important condition cannot be satisfied -- something must be 
done. We envision the following major kinds of accomodation 
to trouble. 
MATCHING: When nothing more specific is found, we can 
attempt to use some "basic" associative memory 
mechanism. This will succeed by itself only in 
relatively simple situations, but should play • 
supporting role in the other tactics. 
EXCUSE: An apparent misfit can often be excused or 
explained, A "chair" that meets all other conditions but 
is much too small could be a "toy." 
ADVICE: The frame contains explicit knowledge about what 
to do about the trouble. Below, we describe an 
extensive, learned "Similarity Network" in which to 
embed such knowledge. 
SUMMARY: If a frame cannot be completed or replaced, one 
must give it up..But first one must construct a well- 
formulated complaint or summary to help whatever 
process next becomes responsible for reassigning the 
subframes left in limbo. 
~TCTIIR~ 
When replacing a frame, we do not want to start 
all over again. How can we remember what was already 
"seen?" We consider here only the case in which the system 
has no specific knowledge about what to do and must resort 
to some "general" strate~. No completely general method 
can be very good, but if we could find a new frame that 
shares enough terminals with the old frame, then some of the 
common assignments can be retained, and we will probably do 
better than chance. 
The problem can be formulated as follows: let E 
be the cost of losing a certain already assigned terminal and 
let F be the cost of being unable to assign some other 
terminal. If E is worse than F, then any new frame should 
retain the old subframe. Thus, given any sort of priority 
ordering on the terminals, a typical request for a new frame 
should include: 
(1) Find a frame with as many terminals in common 
with \[a,b,..,z\] as possible, where we list 
high priority terminals already assigned in 
the old frame. 
But the frame being replaced is usually already a subframe of 
some other frame and must satisfy the markers of it._ss 
attachment terminal, lest the entire structure be lost. This 
suggests another form of memory request, looking upward 
rather than downward: 
• (2) Find or build a frame that has properties 
\[a,b,...,z\] 
If we emphasize differences rather than absolute 
specifications, we can merge (2) and (1): 
(3) Find a frame that is like the old frame except 
for certain differences \[a,b~..,z\] between 
them. 
One can imagine a parallel-search or hash-coded •memory to 
handle (1) and (2) if the terminals or properties are simple 
atomic symbols. (There must be some such mechanism, in any 
case, to support a production-based program or some sort of 
pattern matcher.) Unfortunately, there are so many ways to 
do this that it implies no specific design requirements. 
Although (1) and'(2) are formally special cases of 
(3), they are different in •practice because complicated cases 
of (3) require knowledge about differences. In fact (3) is too 
general to be useful as" stated, and we will later propose to 
depend on specific, learned, knowledge about differences 
between pairs of frames rather than on broad, general 
principles. 
It should be emphasized again that we must not 
expect magic. For difficult, novel problems a new 
representation structure will have to be constructed, and th|8 
will require application of both general and special 
knowledge. 
! 
CI,~I~TES~. CI, R~E~. 6R\]~ R 6EO61~RPI~IC 
~IR~IhOG¥ 
To make the Similarity Network act more "complete," consider 
the following analogy. In a city, any person should be able to 
visit any other; but we do not build a special road between 
each pair of houses; we place a group of houses on e 
"block." We do not connect roads between each pair of 
blocks; but have them share streets. We do not connect ~ 
each town to every other; but construct main routes, 
connecting the centers.of larger groups. Within such an 
organization, each member has direct links to some other 
individuals at his own "level," mainly to nearby, highly similar 
ones; but each individual has also at least a few links to 
"distinguished" members of higher level groups. The result is 
that there is usually a rather short sequence between any 
two individuals, if one can but find it. 
At each level, .the aggregates usually have 
distinguished loci or capitols. These serve as elements for 
clustering at the next level of aggregation. There is no non- 
stop airplane service between New Haven and Sen Jose 
because it is more efficient overall to share the "trunk" route 
between New York and San Francisco, which are the capitols 
at that level of aggregation. 
The non-random convergences and divergences of 
the similarity pointers, for each difference ~ thus tend to 
structure our conceptual .world around 
' (l). the aggregation into d-clusters 
(2) the selection of d_-capitols 
Note that it is perfectly all right to have several capitols in a 
clusterj so that there need be no one attribute common to 
them all. The "crisscross resemblances" of Wittgenstein are 
then consequences of the local connections in our similarity 
network, which are surely adequate to explain how we can 
feel as though we know what is a chair or a game -- yet 
cannot always define it in a "logical" way as an element in 
some class-hierarchy or by any other kind of compact, formal, 
declarative rule. The apparent coherence of the conceptual 
aggregates need not reflect explicit definitions, but can 
emerge from the success-directed sharpening of the 
difference-describing processes. 
The selection of capitols corresponds to selecting 
stereotypes or typical elements whose default assignments 
are unusually useful. There are many forms of chairs, for 
example, and one should Choose carefully the chair- 
description frames that are to be the major capitols of chair- 
land. These are used for rapid matching and assigning 
priorities to the various differences. The lower priority 
features of the clustercenter then serve either as default 
properties of the chair types or, if more realism is required, 
as dispatch pointers to the local chair villages end towns. 
Difference pointers could be "functional" as well as 
geometric. Thus, after rejecting a first try at "chair" one 
might try the functional idea of "something one can sit on" to 
explain an unconventional form. This requires • deeper 
analysis in terms of forces and strengths. Of course, that 
analysis would fail to capture toy chairs, or chairs of such 
ornamental delicacy that their actual use would be 
unthinkable. These would be better handled by the method 
of excuses, in which one would bypass the usual geometrical 
or functional explanations in favor of responding to contexts 
involving art or play. 
.Suppose your car battery ruins down. You believe 
that there is an electricity shortage and blame the generator. 
The generator can be represented as a mechanical 
system: the rotor has a pulley wheel ,driven by a belt from 
the engine. Is the belt tight enough? Is it even there? The 
output, seen mechanically, is a cable to the battery or 
whatever. Is. it intact? Are the bolts tight? Are the brushes 
pressing on the commutator? 
Seen electrically, the generator is described 
differently. The rotor is seen as a flux-linking coil, rather 
than as a rotating device. The brushes and commutator are 
seen.as electrical switches. The output is current along a 
pairof conductors leading from the brushes through control 
circuits to the battery. 
The differences between the two frames are 
substantial. The entire mechanical chassis of the car plays 
the simple role, in the electrical frame, of one of the battery 
connections. The diagnostician has to use both 
representations. A failure of current to flow often means 
that an intended conductor is not acting like one. For this 
case, the basic transformation between the frames depends 
on the fact that electrical continuity is in general equivalent 
to firm mechanical attachment. Therefore, any conduction 
disparity revealed by electrical measurements should make us 
look for a corresponding disparity in the mechanical frame. In 
fact, since "repair ~ in this universe is synonymous with 
"mechanical repair," the diagnosis must end in the mechanical 
frame. Eventually, we might ocate a defective mechanical 
junction and discover a loose connection, corrosion, wear, or 
whatever. 
One cannot expect to have e frame exactly right 
for any problem or expect always to be able to invent one. 
But we do have a good deal to work with, and it is important 
to remember the contribution of one's culture in assessing 
'the complexity of problems people seem to solve. Th e 
experienced mechanic need not routinely invent~ he already 
has engine representations in terms of ignition, lubrication, 
cooling, timing, fuel .mixing, transmission, compression, and so 
forth. Cooling, for example, is already subdivided into fluid 
circulation, air flow, thermostasis, etc. Most "ordinary" 
problems are presumably solved by systematic use of the 
analogies provided by the transformations between pairs of 
these structures. The huge network of knowledge, acquired 
from school, books, apprenticeship, or whatever is interlinked 
by difference and relevancy pointers. No doubt the culture 
imparts a good deal of this structure by its conventional use 
of the same words in explanations of different views of e 
subject. 
Over the past decade, it has become widely 
recognized how important are the details of the 
representation of a "problem space"; but it was not so well 
recognized that descriptions can be useful to a program, as 
well as to the person writing the program Perhaps progress 
was actually retarded by ingenious schemes to avoid explicit 
manipulation of descriptions. Especially in "theorem-proving" 
and in "game-playing" the dominant paradigm of the pest 
might be schematized so: 
I 
I 
I 
t 
I 
I 
t 
1 
I 
t 
I 
! 
! 
! 
,i 
! 
! 
! 
! 
I 
I 
I 
I 
1 
I 
i 
| 
t 
I 
I 
i 
! 
l 
I 
I 
t 
I 
The central goal of 
a Theory of 
Problem Solving is 
to find systematic 
ways to reduce 
the extent of the 
Search through the 
Problem Space. 
Sometimes a simple problem is indeed solved by trying a 
sequence of "methods" until one is found to work. Some 
harder problems are solved by a sequence of local 
improvements, by "hill-climbing" within the problem space. 
But even when this solves a particular problem, it tells us 
little about the problem-space; hence yielding no improved 
future competence. The best-developed technology of 
Heuristic Search is that of game-playing using tree-pruning, 
plausible-move generation, and terminal-evaluation methods. 
But even those systems that use hierarchies of symbolic 
goals do not improve their understanding or refine their 
understanding or refine their representations. But there is a 
more mature and powerful paradigm: 
The primary purpose in problem solving 
should be better to understand the 
problem.space, to find representations 
within which the problems are easier to 
solve. The purpose of search is to get 
information for this reformulation, not -- 
as is usually assumed -- to find 
solutions; orce the space is adequately 
understood, solutions to problems will 
more easily be found. 
The value of an intellectual experiment should be assessed 
along the dimension of success ~ partial success - failure, or 
in terms of "improving the situation" or "reducing a 
difference." An application of a "method," or a 
reconfiguration of a representation can be valuable if it leads 
to a way to improve the strategy of subsequent trials. 
Earlier formulations of the role of heuristic search strategies 
did not emphasize these possibilities, although they are 
implicit in discussions of "planning." 
Papert (1972; see also Minsky 1972) is correct in 
believing that the ability to diagnose and modify one's own 
procedures is a collection of specific and important "skills." 
Debugging, a fundamentally important component of 
intelligence, has its own special techniques and procedures. 
Every normal person is pretty good at them. or otherwise he 
would not have learned to see and talk! Goldstein (AIM-305) 
and Sussman (TR-297) have designed systems which build 
new procedures to satisfy multiple requirements by such 
elementary but powerful techniques as: 
I. Make a crude first attempt by the first order 
met~hod of simply putting together 
procedures that separately achieve the 
individual goals. 
2. If something goes wrong, try to characterize one 
of the defects as a specific (and 
• undesirable) kind of interaction between two 
procedures. 
3. Apply a "debugging technique" that, according to a 
record in memory, is good at repairing that 
specific kind of interaction. 
4. Summarize the experience, to add to the 
"debugging techniques library" in memory. 
These might seem simple-minded, but if the new problem is 
not too radically different.from the old ones, then they have a 
good,chance to work, especially if one picks out the right 
first-order approximations. If the new problem is radically 
different, one should not expect any learning theory to work 
well. Without a structured cognitive map -- without the 
"near misses" of Winston, or a cultural supply of good training 
sequences of problems -- we should not expect radically 
new paradigms to appear magically whenever we need them. 
gO~E F~EhEV~RT F~E~Dm~ 
Abelson, R. P. "The Structure of •Belief Systems." Computer 
Models of Thought an._dd Language. Ed. R. Schank 
and K. Colby. San Francisco: W. H. Freeman, 
1973. 
Bartlett, F. C. Remembering. Cambridge: Cambridge 
University Press, | 967. 
Berlin, I. T.h.e Hedgehog and the Fox. 
American Library, 1957. 
New York: New 
Celce-Murcia, M. Paradigms for Sentence Recognition. Los 
Angeles~ Univ. of California, Dept. of Linguistics, 
197Z 
Chafe, W. First Tech. Report, Contrastive Semantics ProjecL 
Berkeley: Univ. of California, Oept. of Linguistics, 
1972. 
Chomsky, N. "Syntactic Structures." (Ori~nally published as 
"Strukturen der Syntax") Janua Linguarum Studia 
Memoriae, ! 82 (! 957). 
Fillmore, C. J. "The Case for Case." Universals in Linguistic 
Theory. Ed. Bach and Harms. Chicago: Holt, 
Rinehart and Winston, i 968. 
Freeman, P. and A. Newell. "A Model for Functional 
Reasoning in Design." Proc. Second. Intl. Conf. 
o_~nArtificial Intelligence. London: Sept. 1971. 
Gombrich, E H. Ar_!t and Illusion, A_ Study in th.__ee ~ of 
Pictorial Representatio.n. Princeton: Princeton 
University Press, t969. 
Hogarth, W: The A nalys)s of Beauty. Oxford: Oxford 
University Press, 1955. 
Huffman, D. A. "Impossible Objects as Nonsense Sentences." 
Machine Intelligence 6. Ed. D. Michie and B. 
Meltzer. Edinburgh: Edinburgh University Press, 
\] 972. 
Koffka, K. Principles of Gestalt Psychology. New York: 
Harcourt, Brace and World, \] 963. 
Kuhn, T. The Structure Of Scientific Revolutions. 2nd ed. 
Chicago: University of Chicago Press, 1970. 
Lavoisier, A. Elements of Chemistry. Chicago: Regnery, 
\] 949. 
Levin, J. A, Network Representation and Rotation of Letters. 
Publication of the Dept. of Psychology, University 
of California, La Jolla, 1973. 
Minsky, M. "Form and Content in Computer Science." 1970 
ACM Turing Lecture. Journal of the~ ACMp 17, No. 
2 (April 1970), 197-215. 
Minsky, M. and S. Papert. Perceptrons. Cambridge: M.I.T. 
Press, 1969. 
Moore, J. and A. Newell. "How can MERLIN Understand?" 
• Knowledge and Cognition. Ed. J. Gregg. Potomac, 
Md.: Lawrence Erlbaum Associates, 1973. 
Newelli A. Productions Systems: Models .of Control 
Structures, Visual Information Processing. New 
York: Academic Press, 1973. 
Newell, A. "Artificial Intelligence and the Concept of Mind." 
Computer Models of Thought and Language. Ed. R. 
Schank and K. Colby. San Francisco: W. H; 
Freeman, 1973. 
Newell, A. and H. A. Simon. Human Problem Solving. 
Englewood-Cliffs, N.J.: Prentice-Hall, 1972. 
Norman, D. "Memory, Knowledge and the Answering of 
Questio.ns." Loyola Symposium on Cognitive 
Psychology, Chicago, 1972. 
Papert, S. "Teaching Children to be Mathematicians vs. 
Teaching about Mathematics." Int. J. Matk Edu¢. 
Sc.~i. Technol., 3_ (1972), 249-262. 
Piaget, J. Si_~x Psychological Studies. Ed. D. Elklnd. New 
York: Vintage, 1968. 
Piaget, J. 
Pylyshyn, 
and B. Inhelder. The Child's Conception of Space. 
New York: The Humanities Press, | 956. 
Z.W. "What the Mind's Eye Tells the Mind's BraiR" 
Psychological Bulletin. 80 (1973), 1-24. 
Roberts, L. G. Machine Perception of Three Dimensional 
Solids, Optical a..nd Optoelectric Information, 
Processing. Cambridge: M.I.T. Press, 1965. 
Sandewall, E. "Representing Natural Language Information in 
Predicate Calculus." Machine !ntelligence 6. Ed. D. 
Michie and B~ Meltzer. Edinburgh: Edinburgh 
University Press, 1972. 
Schank, R. "Conceptual Dependency: A Theory of Natural 
Language Understanding." Cognitive Psychology 
(\]972), 552-63l. see also Schank, R. and K. Colby, 
Computer Models of Thought and Language. San 
Francisco: W. I-1. Freeman, \] 973.. 
Simmons, R. F. "Semantic Networks: Their Computation and 
Use for Understanding English Sentences." 
Computer Models of Thought and Language. Ed. R. 
Schank and K. Colby. San Francisco: W. H. 
Freeman,. 19'73. 
• Underwood, S. A. and C. L. Gates, Visual Learning and 
Recognition by Computer, T R-_\]22~3 Publications of 
Elect. Res. Center, University of Texas, April, 
1972. 
Wertheimer, M. Productive Thinking. Evanston, IlL: Harper & 
Row, 1959. 
Wilks, Y. "Preference Semantics/' Memo AIM-206, 
Publications of Stanford Artificial Intelligence 
Laboratory, Stanford University, July, 1973. 
Wilks, Y. "An Artificial Intelligence Approach to Machine 
Translation." Computer Models of Thought and 
Language. Ed. R. Schank and K. Colby. San 
Francisco: W. H. Freeman, ! 973. 
I 
! 
t 
| 
I 
I 
'I 
i 
tt 
i 
,I 
I 
I 
t 
I 
I 
I 
t 
1 
