[comp.ai] Blackboard Model of Composition

smoliar@vaxa.isi.edu (Stephen Smoliar) (05/26/90)

In article <16695@phoenix.Princeton.EDU> eliot@phoenix.Princeton.EDU (Eliot
Handelman) writes:
>"Music compoistion as hypothesis formation: a blackboard concept of
>creativity" 
>
>by
>
>Otto Laske
>
>--a summary and an informal chat by E. Handelman
>
I was very glad to see Eliot post this article.  I also happen to have a copy
of the paper in question (which, as Eliot mentioned only is passing, was
delivered at an AI conference in Prague last year).  Because some of the
points of discussion concern artificial intelligence as much as they do
music, I am taking the liberty of cross-posting this to comp.ai.  I shall
try to make sure that there is sufficient context for new readers.
> 
>Laske has a new paradigm: blackboards. He explains: "...a mental
>activity is carried out in parallel by a multitude of agents
>communicating with each other via a central short-term memory called a
>blackboard." Laske wants to see if this is a good thing for
>composition. I'll briefly summarize. commenting below.
>
In the past (for example JOURNAL OF MUSIC THEORY, Volume 30, Number 1) I have
criticized Laske for being too enamored of the artifacts and terminology of
artificial intelligence without necessarily having a clear idea of the
intentions being such artifacts and terminology.  I find Laske's "discovery"
of blackboards slightly amusing because in a 1976 JOURNAL OF MUSIC THEORY
article (Volume 20) I tried to interpret his work at the time in the context
of work in speech recognition . . . particularly the Hearsay effort at
Carnegie.  This turned into one of the first major applications of a blackboard
architecture.

Nevertheless, I think it is a big mistake to try to hold up a blackboard as
some magic device which is going to solve all sorts of old problems.  When
all is said and done, a blackboard is nothing more than a vast global data
base which may be manipulated by an equally vast repertoire of productions.
The Hearsay effort was not so interesting for HAVING a blackboard as it was
for the approach it took to STRUCTURING the blackboard.  Indeed, we can begin
with the observation that such structuring was a good thing (or, conversely,
that a vast unstructured pool of data objects is NOT a particularly good
thing).  Thus, for all intents and purposes, committing yourself to having
a blackboard does not amount to very much unless you also commit yourself
to how it will be structured.
>
>Laske wants to make a model of 1. WHAT musicians know, and 2. HOW this
>knowledge is used. The former Laske terms "competence", the latter
>"performance."
>
Like many of us, Laske has read his Chomsky.  I first came across this
distinction in ASPECTS OF THE THEORY OF SYNTAX.  Upon returning to this
book, I discovered, to my surprise, that Halle and Stevens were discussing
the competence-performance distinction with respect to speech recognition
in a 1962 article in the IRE TRANSACTIONS IN INFORMATION THEORY.

Thus, it would seem that Laske is trying to take some of the things known
about speech recognition and adapt them.  If we were dealing with LISTENING
to music, then there might be some grounds for such analogical reasoning;
and this was the sort of case I was trying to make in my earlier JOURNAL
OF MUSIC THEORY article.  However, as he informs us in his title, Laske
is interested in COMPOSITION, rather than LISTENING.  Indeed, in another
article (from that wonderful issue of INTERFACE which provided the Balaban
article which got much of this discussion going in the first place) Laske
went so far as to argue that the teaching of composition is placing far too
much emphasis on listening.  Thus, it is most unclear just what lies at the
foundation of Laske's thinking here.

Let's put matters another way:  blackboards are not a paradigm.  Blackboards
are simply an artifact of a particularly way of thinking about AI problems.
If Laske wants to turn to AI as a paradigm, then he should be looking for some
particular means by which AI deals with a specific problem domain and then
argue for an analogy between that domain and musical composition.
Unfortunately, I do not think he has EVER done this in any of his
publications, which means that, for all intents and purposes, it
is rather unclear just what he IS doing.

>The competence model consists of a blackboard, a knowledge base, and a
>data acquistion module.
>
>Blackboard: post hypotheses about current state of piece here.
>Knowledge Base: must know about 1. planning, 2. scheduling, 3. music.
>Data Acquisition Module: not explained.
>
This is all pretty hollow use of vocabulary.  There are times when I wish we
could call a moratorium on use of the word "knowledge base."  It is turning
out to be an excellent way to deceive anyone whose working knowledge of AI
is weak.  I suppose it is this attitude which has driven me towards writers
like Minsky, who tend to scrupulously AVOID words like "knowledge" when writing
about artificial intelligence.

If Laske believes he can have a knowledge base which "knows about" planning,
scheduling, and music, then he is probably sucker enough to buy the Brooklyn
Bridge (probably from a sales representative of your favorite commercial AI
house).  Any AI student would be able to tell him that we still have a long
way to go in teasing out just what we mean by knowledge of either planning
or scheduling.  We may be able to do impressive things in appropriately
restricted problem domains, but we are still some distance from being able
to generalize any successes of the past into any theories concerned with
knowledge of either planning or scheduling.

Being sloppy about terminology is sort of like eating potato chips.  Once you
start, it's hard to stop.  Having sailed over planning and scheduling as if we
already knew all about them, Laske sees no trouble in adding music to his
knowledge base.  Does he have the slightest idea what music knowledge is?
Do any of us?  Some of us are still trying to get a handle on what constitutes
musical BEHAVIOR.  We might grudgingly admit that musical knowledge amounts to
whatever competence enables such behavioral performance;  but, if we are at all
honest, we also have to admit that our knowledge of that behavior is SO limited
that we are a far cry from approaching any questions of competence.  In
fairness to Laske, however, it SHOULD be noted that he seems to want to
give "equal time" to matters of performance:
>
>The performance model consists of 1. an interpreter and 2. a
>scheduler. 
>
>1. interpreter -- knows how to carry out compositional plans. 
>2. scheduler -- post, retract and alter hypotheses.
>
Unfortunately, these are more shallow words.  Furthermore, they seem to
indicate that Laske feels that talking about competence is prerequisite
to talking about performance.  I would argue that this is absolutely the
wrong way to approach the issue.  The fact is that performance is about
the only thing for which we have any concrete evidence at our disposal.
Laske should be worrying about how to talk about evidence of musical behavior.
(To some extent, he has done this in the past.  He has even done protocol
studies in which he has attempted to collect such evidence systematically.)
Until we converge on some language for talking about performance, it makes
little sense to try to talk about competence.  The danger is like trying to
build a bridge from both banks of the river without a clear idea of where the
two pieces are supposed to join.  Another way of putting it is that a language
for talking about competence should REFLECT the language for talking about
performance rather than impose PROPTER HOC constraints.

Many of these comments actually overlap some of Eliot's concluding assessments.
However, I felt it was necessary to review some of these observations in a
slightly different light.  Still, Eliot has made one very powerful point which
music be emphasized:
>
>o Model stresses composition as "problem solving," though nature of problem
>  isn't  described. Method of solution is described. First identify
>  problem, then describe solution.
>
There is a standard joke about AI results:  each is a solution in search of the
right problem.  Laske has fallen into the standard trap.  He would like to
follow where technology leads in hope of finding something.  In general, it
is healthier to start out with some goals . . . even if those goals must be
subsequently abandoned.
>
>o Model is a masturbation fantasy concerning the future of AI. 
>
Well, it is nice to see Eliot close with the imprimatur of his style of
argument!  Actually, one could also read this as a commentary on the sad
PRESENT of AI.  It is very easy to misunderstand what AI is all about.
Unfortunately, such misunderstandings are often cultivated by the very
people who practice AI.  While this is often done in the name of attracting
customers or funding agencies, it is often overlooked that there may be
innocent bystanders who are caught up in all this confusion of accomplishment
and wishful thinking.  Laske seems to have been such an innocent bystander, and
I worry about how many more are out there who have been similarly deluded.

=========================================================================

USPS:	Stephen Smoliar
	USC Information Sciences Institute
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"By long custom, social discourse in Cambridge is intended to impart and only
rarely to obtain information.  People talk;  it is not expected that anyone
will listen.  A respectful show of attention is all that is required until
the listener takes over in his or her turn.  No one has ever been known to
repeat what he or she has heard at a party or other social gathering."
					John Kenneth Galbraith
					A TENURED PROFESSOR