2pat S ZsXr/tiVO/O - Stacks are the Stanford

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<BARR>MK2.
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f*i/OocO/£Zx?2—
Tue 6-Feb-79 9: 4IPM
/? 2pat S ZsXr/tiVO/O
KNOWLEDGE
. crown
( 10, 10, 10)
After discussing what meta-knowledge might mean, and what
kinds of things can be "known about knowledge", we review some
MX is
psycho studies for a feeling of the epistomology of MX.
an intrinsic part of human cognition
Review the reasons for
developing techniques for rep. of MX in All as well as extent/limits
of those techniques.
. endcrown
OMeta-knowledge is knowledge about knowledge. >
begin to explore exactly what this sentence might mean.
The common understanding is something like this
This paper will
.
crown (10, 10, 10)
Knowledge is an
accumulation of some sort, of "facts" about the world.
Meta-knowledge is the same kind of accumulation of
but instead of being about the world, they are about other
other knowledge.
. endcrown
.skip cont inue
This explanation appeals to our intuitive notion of knowledge being
<+about the world>. referring to a morphism between the world of our
perceptions and our storage of information.
It is my belief that these intuitions are no longer useful in the
study of cognition, that in fact they lead to serious confusion.
In going through examples of Al systems and psychological studies
that explore meta-knowledge. the difficulties will be examined.
-
see note on why MX breaks the circle. .
it to be "about".
. there
is nothing for
The use of meta-knowledge in expert Al systems like MYCIN for
facilitation of explanation and acquisition is, a key
We will discuss
breakthrough in the design of intelligent systems.
why later, but first let's deal with an easy preliminary issue.
. glitch
You have to discuss the point that "knowing not", for instance,
best
described as a "fact" in the head.
But then again, neither
is not
is "snow is white".
endg l i tch
.
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What is Knowledge?
"Knowing" is intimately tied to behavior, and thus to process.
When we say that an animal knows something, we mean that it acts in a
certain way that is different than it would if it didn't.
The fact that
there is some piece of knowledge or fact or
is inferred by
us:
Used to explain the difference (change in the animal) in a simple
way that we all understand.
Pseudo-process
(Giraffes)
In Al, we have established for ourselves that the meaning of a
representation is intimately tied to the process that Interprets it. and
it does not exist without that context.
But we still talk about adding
links to a net, or facts to a data-base: assuming that the Interpreter
is fixed.
But the Interpreter also represents knowledge, about how to use
the other knowledge.
And if this "meta-knowledge" is also aquired. then
the interpreter may not be an unchanging entity.
Interpreter: Declarative/Procedural vs. Explicit/Implicit
TEIRESIAS
Flavell
Split personalities, Post-hypnotic suggestions
HAM like vs EPAM like models
Why
is it useful to think about knowledge
knowledge
"objectively
To begin with, let us examine the idea that
Cognition is the processing
of Oinf ormat ion>, some internally
stored symbolic representation of facts about the real world.
This pervasive view of intelligence has assimilated
the architecture for computer memory associated with -Ciref vonNeum4o>
a separate, relatively low speed, passive
storage distinct from the processors (arithmetic, logical. I/O. etc. )
that manipulate it.
This is the way we have come to think about and build
computers, but it was from
the beginning only a compromise forced by the relative
cost of active (switching) elements and their
interconnections.
To some extent, the brain has probably realized
similar compromises, due to similar constraints -Cpref vonneumsB>, but not
necessarily as far as the complete isolation of memory from processor
as in current computer architectures. ssNor is it necessarily true that
these constraints still apply to computer hardware design.
Micro-electronic techology has inverted the cost ratio of components
and interconnections, and the idea of distributed memory is a natural
consequence that has been pointed out by several authors.
(■Clref suther77>; -Clref rgsmi th77> ) . ■*
- Hubel and
-
Weisel,
frog's eye
machines as formal symbol manipulators
Al Insights: Logic, Production Systems
- explict vs. objective knowledge
->
symbolic
"representation
f
<BARR>MK2.
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representation:
A* la CS 365.
Tue 6-Feb-79 9: 4IPM
knowledge as an object in the head
.mark Objective Knowledge as Ascription
What's really going on here?
What do we mean when we say that someone knows something?
When we see people driving a car or playing chess, we say that they
"know how," and we interpret this in terms of their "having" the
But the behaviors we've actually observed, like
requisite knowledge.
learning, remembering, making
solving problems, and
task,
crudely explained by
the
are
and
are
complex
only
performing
saying that the knower "has" the requisite "knowledge" in his head.
It is the way we talk and think about people
that leads to the "knowledge as object" metaphor.
Just as we say
people have a love in their heart or have a pain in their neck, we
objectivize the fact that they know how to do something and stick it in their
head.
-Ciref mccar77> refers to this as "ascription of knowledge to others. "
. glitch
Must
. endg 1 itch
check the McCarthy paper.
In the next section I will discuss some alternative metaphors
But I am not proposing that these metaphors
for understanding knowledge.
are in any sense more useful.
In
the remainder of the paper will
propose the extension of an "objective knowledge" description to the
The utility of
"interpretive" parts of our models of human cognition.
this metaphor stems from our limitations in understanding complex systems.
It should be used as a tool for describing those systems, rather than being
an assumption about the way those systems are.
stoptext
-
language is "objective"
why is it useful to think about X this way
problems with "objective" knowledge"
no evidence for facts in the head
(
dec larati vely
)
assume sufficient interpreter,
how do we use the
evidence
no
for the world out there, besides knowledge
startte x t
.mark Other Metaphors for Knowledge
The Problem
I am concerned with the characterization of Cognition and
In particular, there is a generally accepted idea
Cognitive processes.
of what memory is in such systems, and I have poked at that notion a bit
and found it unsatisfying.
To wit,
Memory in Man and Machine is a storage device of some sort,
and the Cognitive processes have STORE and FETCH access to it.
I
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Tue 6-Feb-79 9: 4IPM
This is the basic yon Neumann idea of machine architecture.
Our machines
are still built that way.
Current theories in Information Processing
Psychology assume that that is the way the mind works.
Psycholgical
always
assumption,
theories haven't
made that
nor are computers necessarily
going to always be built that way.
SR theory, the rat in a maze
Gestalt theory, gestalt closure
Neuronal development
Architecture, distributed memory,
self-organization
Compare this conception of memory as a storage device
with that implied by a stimulus-response view of behavior.
Here memory (of the appropriate response and the conditions that make
appropriate) is viewed as a more-or-less
structural change in the organism.
Learning not only changes the
■C+contents of memory>, but the whole structure of the organism's
it
cognitive processes:
An animal that remembers the experience of an electric shock in a
T-maze context will seem to <+see> and 01earn> differently
on returning to the maze than an untrained animal.
Clearly this is an oversimplification of Behaviourism, but the
important point is that it is always possible to view
the acquisition of knowledge as a modification to a program.
as opposed to an addition to a data base that is used by an unchanging
interpreter.
-
memory
biology,
behavior,
process
structural change in the organism
S-R psychology
knowledge as procedures
how can you know a process
construction of reality
Most everyone agrees that to some extent, we construct our personal
reality.
There are a lot of ways of looking at this issue: psychological,
anthrop log ical, sociological, linguistic, philosophical, etc.
The way that
it relates to the material presented here is that if we give up the notion,
that Memory is a passive storage device, and instead view it as an aspect
of Cognitive behavior that is a constantly changing process, we have not
evidence that there is a fixed external world that we record information
about.
/
<BARR>MK2.
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Conclusions about
Tue 6-Feb-79 9: 4IPM
knowledge
?The proceding discussion of the nature of knowledge is certainly
naive, and may very well be wrong.
Before going on the meta-knowledge.
conclude,
I would like to
and I don't believe this is wrong, that the
conception of knowledge as an accumulation of facts is only one way of
Furthermore, that although it has served well
looking at knowledge.
as an epistomolgy for (classical) physics, for instance, to proceed in
the study of cognition we will find other conceptions of the nature
of knowledge useful.
maybe
why?
just treat obj.
k.
differently?
/
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Tue 6-Feb-79 9: 4IPM
.mark Meta-knowledge
And it is also possible to view an interpreting program in terms
knowledge about its data base, called --:+meta~knowledge> in Al these
days.
Specifically, the interpreter must in some sense"
know the extent and limit of available
knowledge, what facts are relevant in a given situation,
how dependable they are, and how they are to be used.
This kind of knowledge is usually built implicitly into the interpreter
of an Al system, but can be separated out and declared explicitly, leaving
a residual interpreter whose job is to operate on the meta-knowledge.
This duality between meta-knowledge and interpreting process
has come to the forefront in
Al Representation Theory through the development of representation
languages which allow explict and flexible statements of meta-knowledge
in their semantics.
If all of the interpreter's knowledge, formerly encoded in implicit,
procedural
is made explict, as meta-knowledge, the interpretive
of
"code" that
remains
which,
is relatively trivial, something like a scheduler of processes
in turn, include meta-level interpretive information in their data.
. glitch
I have become familiar with the explicit use of
meta-knowledge through
Terry Winograd and KRL ({lref bobr77>).
The best treatment of the
relationship of representation and interpreting process is Brian
Smith's recent work on Knowledge Representation Semantics (-Clref bsmith77>)
I will return to this discussion in Section -(.'yon krl>.
endg 1 i tch
.
*
Thus, meta-knowledge and interpretive process can be
viewed as playing the same role in Cognition:
specifying how to find
the relevant knowledge and how to use it.
The distinction drawn between
is like the familiar distinction between declarative and
procedural knowledge representations, only one level up:
The interpreter is procedural knowledge about how to reason with the
base level knowledge, and meta-knowledge is its declarative form (see -Clref wino
And when we consider our cognitive processes as declarative knowledge,
meta-knowledge, it is natural to ask how we acquire it: do we learn to
reason, and to remember?
With this Duality of declarative meta-knowledge and interpreting
process mind, it is fruitful to explore
an epistemology that does not postulate a real, <+ob jec t i ve> world
which we observe and store facts about.
For if indeed our observations
are recorded not as facts in a passive memory, but in the very process
that is supposed to be doing the observing, the Oreal worldsmay be a simplification that can lead to
confusions in the study of Cognition.
An alternative epistemology, which I
learned of through the uiork of the biol og i st/cy berneti ci st Humberto
Maturana, has served
as the inspiration for my own exploration of the nature of process in
The name C+radical construe tivism> has been used by
Cognition.
■Ciref glas77> to describe this view.
Maturana recognizes the need
}
'
<BARR>MK2. KNOWLEDGE; I
Tue 6-F'eb-79 9: 41PM
to view memory as a structural change in the organism, but doesn't
differentiate between the influencea of the external world
and those induced by other states
of nervous system activity.
From this C+closure> property of the
nervous system, he develops a theory of consciousness, including a
formal description of the Observer.
-
relation to (identy with) cogntive process (MXI)
explicit form of implicit knowledge in an interpretive process
syntactic vs. semantic MX
Consider the well-known human behavior called the t ip-of-the-tongue
phenomenon:
. crown ( 10, 10, 10)
You run into someone you have met once
and you
can't remember his name.
You remember
very well your first meeting at a Mew Year's Eve party in
and
that he is the brother-in-law of your wife's
boss.
Then you remember that he has a foreign-sounding name.
It rhymes
spaghetti.
with
.endcrown skip continue
You could use all of this knowledge in trying to recollect his name.
And you would certainly say that you "know his name", even thought you
can't recall it:
You "know that you know it. "
introspective
This kind of
evidence
suggests a major role for Ometa-knowl ed ge> in human reasoning:
Knowledge about the extent, reliability.
importance, and history of the knowledge we "have" of the world.
glitch
Better fix up this to be clear that MX is a way of describing
this behavior.
Refs: (-Clref col 1 ins !mk >, -{lref teiresias>).
col 1 ins ! gentner} and -Clref flavell}).
teiresias.}, -Clref krl}, -Clref brachman}).
endg l i tch
(■Clref
("Clref
.
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- <BARR>MK2.
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Tue 6-Feb-79 9: 4IPM
Here is a partial list of the kinds of things that might be useful to
know, about what we know:
. crown
(5, 5,
5)
«Extent>.
In particular, knowledge about what we don't know.
To answer the
question <+What is Paul Newman's telephone number?> you might reason
that "If I knew Paul Newman's number, I would know that I knew it,
because it is a notable fact. "
«Defaults>.
We have expectations about objects and events
that we encounter that can be viewed as default values for the
parameters of new data structures.
How important some facts are relative to
«Cr i ter ia 1 ity >.
a given conclusion: A trunk is more indicative of an elephant than
are four legs.
Explicit knowledge about what kinds of knowledge
«Relevance>.
may be relevant to certain tasks.
This may come in the form of links
between data structures, or groupings of structures into larger structures.
■".XHistory>.
Knowledge about the source, age, and development
structure.
of the data
OCRel iabil ity>.
How certain this knowledge is.
If it is
contradicted by other observations and
when it should be abandoned.
"C-CRepresentat ion>.
Knowledge of the representation
since it is necessary before
the data structures can be modified.
But explicit information about
the representation is also possible, and it is especially useful for multiple
uses of the same data structures.
formalism is always available implicitly,
<<Meta-cogni t ive knowledges.
This is knowledge of the
capabilities of the system.
We humans learn this kind of information
from experience {pref flavell}, but Al systems might also benefit
from knowledge of their own performance.
As an
example, -Ciref bobr7s> discusses a robot who is planning a trip.
His knowledge that he can read
the street signs along the way to find
is meta-cognitive knowledge.
. endcrown
out where he is
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,j
How has it been done?
what form has
- examples
from
- KRL,
MX taken in Al systems
Al systems
McCarthy, FOL
Brian Smith
The people Brian mentioned
Collins: Al and Learning Systems, Reasoning from Incomplete X
psych
feeling of knowing
Flavell's meta-cognitive knowledge
Collins & Gentner
what if any unifying design principles can be discovered
Why
is meta-knowlege useful
-
knowledge about knowledge and the interpretive process:
an interpreter is "implicit" knowledge about the things it
interprets.
sometimes it is useful to have "explicit"
knowledge about the "database".
this is meta-knowledge
(see Winograd's "procedural-declarative controversy")
in fact it is essential for certain classes of activities,
how can we characterize this class?
Problems with MX
-
the problem of circularity,
what is meta to what
MX and Memory
Critique and
the search
for a uniform representation