Re: comments on AI

John Yen (yen@cs.tamu.edu)
Sat, 26 Sep 1998 23:00:39 +0200 (MET DST)

Dear Prof. Meystel,

Thank you for sharing your thoughts about AI and soft computing.
I simply would like to point out that the ``AI community'' is
changing. During the President Address of AAAI conference this
year, for example, Dr. David Waltz raised serious issues about
purely relying on logic. Two years ago, Dr. Tom Mitchell also
criticised a machine learning paradigm founded in logic (explanation-based
learning) during his AAAI keynote speech. I considered these
significant messages, even though they may not be shared by all
in the AI community.

The AI community is also much more open-minded these days. I think
it is our responsibility to show and demonstrate how soft computing
and AI can be combined synergistically to push the technology
frontier of information technology.

Cheers,

John

>From alex@cerebrum.impaqt.drexel.edu Mon Sep 21 22:34:45 1998
>Date: Mon, 21 Sep 1998 21:35:23 -0400 (EDT)
>From: Alexander Meystel <alex@cerebrum.impaqt.drexel.edu>
>Sender: Alexander Meystel <alex@cerebrum.impaqt.drexel.edu>
>Reply-To: Alexander Meystel <alex@cerebrum.impaqt.drexel.edu>
>Subject: Re: comments on AI
>To: bisc-group@cs.berkeley.edu
>Mime-Version: 1.0
>
>Dear BISCers:
>
>Lotfi's letters about AI remind us about the need to demonstrate clearly
>the pitfalls of its (AI's) existing curriculum and attitudes. One of the
>most important issues neglected by AI is the issue of granularity
>(resolution, scale).
>
>Soft Computing illuminates the relationships between AI and Control
>bodies of knowledge in a specific way. It turns out, that granularity of
>knowledge directs ALL CASES of problem solving efforts into the
>multigranular (multiresolutional, multiscale) direction.
>
>This leads to a number of interesting and important consequences.
>
>Assuming, a robotic problem is given (which should have
>planning/control/actuation/sensing/man-machine interaction intertwined).
>It turns out that "planning" appeals to a particular resolution
>(granularity), control evokes a higher resolution, its realization boils
>down to even a higher resolution of knowledge.
>
>Interesting resemblances can be observed in a multiplicity of practice
>related problems. The following properties can be stated for a
>multiresolutional (multigranular) analysis of a problem:
>1. The degree of refinement (resolution) is growing top-down.
>2. The time scale (the "tick" of the clock) is reducing top-down.
>3. The degree of dynamics to be taking in account is growing top-down).
>
>Any problem requires addressing at least three levels of resolution:
>1. The one to which the minimum model of the system is related
>2. The lower resolution level: the one where the goal of the problem is
>formulated together with the cost-function of interest and the
>constraints of importance.
>3. The higher resolution level: the one where the results of the problem
>solving are supposed to be implemented, realized, and refined.
>
>This leads to a set of conclusions which can be considered instructive ones.
>1. Even if the problem formulation does not require any high degree of
>dynamics to be taken in consideration, at the next adjacent level below,
>the dynamics should be taken in consideration in a higher degree.
>2. Thus, any AI problem embeds the dynamics as the high resolution
>explanation either for the parameters or for the rules of action.
>3. Thus, dynamics is embedded in any AI problem.
>4. Thus, the knowledge in "Control Theory" should be a prerequisite for
>the advanced knowledge of AI and should be recommended to any specialist
>in AI.
>
>AI community is notorious about its orientation toward decoupling the
>planning and control problems (although some outstanding AI researchers
>are trying to resist this tendency, like T. Dean, S. Russell, the general
>attitude is clear).
>
>In my view, it is linked with underestimating the multigranular character
>of Knowledge and the associated problem-solving processes.
>
>Alex Meystel
>
>
>
>
>

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