scott@bgsu.CSNET (Tom Scott) (06/19/86)
The moderator of the AI-List has made an impassioned plea for
help. I would like to help, but before I offer to start a new
Arpanet, Csnet, or UUCP newsgroup, I'd like to put forth an
organization to Ken's list of possible new newsgroups. This
organization comes from the Japanese side of the Pacific, and is
outlined by Brian Gaines in a recent article, "Sixth Generation
Computing: A Conspectus of the Japanese Proposals" ("SIGART
Newsletter", January 1986, pp. 39-44).
Figure 1 of the article, complemented by the fundamental
topics that I've added for the sake of completeness, cuts the cake
thusly:
Theoria | Praxis | Techne
------------ | -------------------- | --------------------
| Expert systems | Pattern recognition
Physiology | | Cognition
| Machine translation | Learning
Psychology | systems | Problem solving
| | Natural language
Linguistics | Intelligent CAD/CAM | Image processing
| systems | Speech recognition
Logic | | Man-Machine interface
| Intelligent robotics |
=============================================================
| Managerial | Expert systems
Epistemology | cybernetics |
| Decision support | Development languages
Modern logical| systems | and environments
metaphysics | Information |
| retrieval systems | Computing/knowledge
Vedic Science | | machines
=============================================================
THE UNIFIED FIELD OF ALL POSSIBILITIES
This is the world of the sixth generation: knowledge science
and knowledge systems. The fifth generation, which deals mainly with
the daily realities of knowledge engineering and expert systems, as
well as with the advanced research and development of VLSI
architectures for the processing of Prolog code and database systems,
is distinct from the sixth generation.
To get a better feel for these distinctions, I'd like to
suggest the following homework assignment for new newsgroup
moderators: (1) Read Brian's article. (2) Read the abstract of the
paper that I'll be presenting to the sixth-generation session at the
1986 International Conference on Systems, Man, and Cybernetics
(Atlanta, October 14-17); the abstract is appended to this message.
(3) Think before you flame; then write back to me or to this newsgroup
and share your thoughts.
We are children of the cybernetic revolution and we are
witnessing the rising sunshine of the Age of Enlightenment.
Tom Scott CSNET: scott@bgsu
Dept. of Math. & Stat. ARPANET: scott%bgsu@csnet-relay
Bowling Green State Univ. UUCP: cbosgd!osu-eddie!bgsuvax!scott
Bowling Green OH 43403-0221 ATT: 419-372-2636
* * * Abstract of the sixth-generation SMC paper * * *
KNOWLEDGE SCIENCE
The Evolution From
Fifth-Generation Expert Systems
To Sixth-Generation Knowledge Systems
Theory, practice, technology--these are the makings of a full vision
of knowledge science and sixth-generation knowledge systems. Prior to
the establishment of research and development projects on the Fifth
Generation Computing System (FGCS), knowledge science did not exist
independent of knowledge engineering, and was conceptualized only in
technological terms, namely, expert systems and "machine architectures
for knowledge-based systems based on high-speed Prolog and relational
database machines" (Gaines 1986).
Although the design and development of fifth-generation
machines and expert systems will continue for years to come, we want
to know now what can be done with these ultra-fast architectures and
expert systems. What kinds of knowledge, other than the knowledge of
domain experts in fifth-generation expert systems, can be acquired and
encoded into sixth-generation knowledge systems? What can be done on
top of fifth-generation technology? How can fifth-generation
architectures and expert-system techniques be extended to build
intelligent sixth-generation knowledge systems?
Beyond the fifth generation it is necessary to envision
practical applications and theoretical foundations for knowledge
science in addition to the technological implementation of machine
architectures and expert systems. This paper discusses the full
three-part vision of knowledge science (theoria, praxis, and techne)
that is emerging around the world and has been treated by the Japanese
under the title Sixth Generation Computing System (SGCS).
Theoria: As indicated in Brian Gaines's article, "Sixth
Generation Computing: A Conspectus of the Japanese Proposals"
("ACM-SIGART Newsletter" January 1986), the theoretical foundations of
knowledge science are arranged in levels, proceeding downward from
physiology to psychology to linguistics to logic. Continuing in this
direction toward deeper foundations, the field of knowledge science
embraces epistemology and modern logical metpahysics. On the
empirical side of the deep foundations is the probability-based
epistemology of pragmatism, explicated in Isaac Levi's "The Enterprise
of Knowledge" (1980); on the transcendental side are Immanuel Kant's
"Critique of Pure Reason" (1781-87) and Edmund Husserl's "Formal and
Transcendental Logic" (1929). A simplified diagram of the four main
divisions of mind, based on one sentence of the Critique ("Beide sind
entweder rein, oder empirisch": B74), is:
Understanding Sensibility
|
E Knowledge Images
m of --------> Objects
p objects |
|
----------------------+-----------------------
T |
r Pure concepts Schemas Pure forms of
a (categories) --------> intuition
n and principles | (space and time)
s |
Praxis: The SGCS project is also concerned with the practical
applications of knowledge science. These applications are organized
under four headings: expert systems, machine-translation systems,
intelligent CAD/CAM, and intelligent robotics. Another way of
organizing the applications of knowledge science in terms familiar to
the IEEE Systems, Man, and Cybernetics Society is: managerial
cybernetics, organizational analysis, decision support, and
information retrieval. Stafford Beer's "The Heart of Enterprise"
(1979) is the focal point of our discussion of knowledge-science
praxis.
Techne: The SGCS project targets eight technological areas as
the basis for the future research and development of sixth-generation
knowledge systems: pattern recognition, cognition, learning, problem
solving, natural language, image processing, speech recognition, and
man-machine interfacing. To fully realize the R&D potential of these
eight areas, sixth-generation knowledge scientists must be on friendly
terms with the following areas of expertise from fifth-generation
knowledge engineering:
(1) Expert systems.
(a) Concepts and techniques for the acquisition,
representation, and use of knowledge.
(b) The software engineering of knowledge systems,
including a methodology for the building of expert
systems and the management of expert-system
development teams.
(c) Expert systems and shells.
(2) Three levels of systems and software.
(a) Production systems (e.g., ITP, Prolog, and OPS83).
(b) Traditional AI/KE languages (e.g., Lisp and Prolog).
(c) Development environments and utilities (e.g., Unix, C,
and Emacs).
(3) The knowledge engineer's technical intuition of a
computational knowledge machine.
(a) Lambda Consciousness, based on the idea of a Lisp
machine.
(b) Relational database machines.
(c) Prolog machines.
The paper includes observations from the experience of the
University of Wisconsin-Green Bay in its attempts to establish a
regional knowledge-engineering and knowledge-science resource center
in the Northeastern Wisconsin area.
* * * Finis * * *