fishwick@uflorida.cis.ufl.EDU (Paul Fishwick) (09/17/88)
An inquiry into concepts of "state" and "change":
In browsing through Genesereth's and Nilsson's recent book "Logical
Foundations of Artificial Intelligence," I find it interesting to
compare and contrast the concepts described in Chapter 11 - "State
and Change" with state/change concepts defined within systems
theory and simulation modeling. The authors make the following statement:
"Insufficient attention has been paid to the problem of continuous
actions." Now, a question that immediately comes to mind is "What problem?"
Perhaps, they are referring to the problem of defining semantics for
"how humans think about continuous actions." This leads to some
interesting questions:
1) Clearly, the vast literature on math modeling is indicative of
"how humans think about continuous actions." This knowledge is
in a compiled form, and use of this knowledge has served
science in an untold number of circumstances.
2) If commonsense knowledge representation is the issue then we
might want to ask a fundamental question "Why do we care about
representing commonsense knowledge about continuous actions?"
I can see 2 possible goals: One goal is to validate some given
theory of commonsense "continuous action" knowledge against
actual psychological data. Then we could say, for instance, that
Theory XYZ reflects human thought and is therefore useful.
I don't think it would be useful to increase our knowledge of
mechanics or fluidics, for instance, but perhaps a psycho-therapist
might find this knowledge useful. A second goal is to obtain
a better model of the continuous action (this reflects the
"AI is an approach to problem solving" method where one can
study "how Johnny reasons when balls are bounced" and obtain
a scientifically superior model regardless of its actual
psychological validity). Has anyone seen a commonsense model
of continuous action that is an improvement over systems of
differential equations, graph based queueing models (and other
assorted formal languages for systems and simulation)?
Obviously, I'm trying to spark some inter-group discussion and so I hope
that any responses will post to both the AI group (comp.ai) AND
the SIMULATION group (comp.simulation). In addition (sci.math) and
(comp.theory.dynamic-sys) may be appropriate.
I believe that Genesereth and Nilsson are quite correct that "reasoning
about time and continous actions" is an important issue. However, an
even more important issue revolves around people discussing
concepts about "state," "time," and "change" by crossing disciplines.
Any thoughts?
-paul
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+------------------------------------------------------------------------+lee@uhccux.uhcc.hawaii.edu (Greg Lee) (09/17/88)
From article <18249@uflorida.cis.ufl.EDU>, by fishwick@uflorida.cis.ufl.EDU (Paul Fishwick): " " 2) If commonsense knowledge representation is the issue then we " might want to ask a fundamental question "Why do we care about " representing commonsense knowledge about continuous actions?" " I can see 2 possible goals: One goal is to validate some given " ... To reason about continuous actions where the physics hasn't been worked out or is computationally infeasible. How about that as a third goal? " Obviously, I'm trying to spark some inter-group discussion and so I hope " that any responses will post to both the AI group (comp.ai) AND " the SIMULATION group (comp.simulation). In addition (sci.math) and " (comp.theory.dynamic-sys) may be appropriate. Tsk, tsk. Left out sci.lang. The way people think about these things is reflected in the tense/aspect systems of natural languages. " I believe that Genesereth and Nilsson are quite correct that "reasoning " about time and continous actions" is an important issue. However, an " even more important issue revolves around people discussing " concepts about "state," "time," and "change" by crossing disciplines. " Any thoughts? In English, predicates which can occur with Agent subjects, those capable of deliberate action, can also occur in the progressive aspect, expressing continuous action. This suggests some connection between intent and continuity whose nature is not obvious, to me anyway. Greg, lee@uhccux.uhcc.hawaii.edu
smryan@garth.UUCP (Steven Ryan) (09/19/88)
>Foundations of Artificial Intelligence," I find it interesting to >compare and contrast the concepts described in Chapter 11 - "State >and Change" with state/change concepts defined within systems >theory and simulation modeling. The authors make the following statement: >"Insufficient attention has been paid to the problem of continuous >actions." Now, a question that immediately comes to mind is "What problem?" Presumably, they are referring to that formal systems are strictly discrete and finite. This has to do to with `effective computation.' Discrete systems can be explained in such simple terms that is always clear exactly what is being done. Continuous systems are computably using calculus, but is this `effective computation?' Calculus uses a number of existent theorems which prove some point or set exists, but provide no method to effectively compute the value. Or is knowing the value exists sufficient because, after all, we can map the real line into a bounded interval which can be traversed in finite time? It is not clear that all natural phenomon can be modelled on the discrete and finite digital computer. If not, what computer could we use? >Any thoughts?