Fuzzy Set: 1965 … Fuzzy Logic: 1973 …
BISC: 1990 … New Direction: 2000 - ….
History; BISC During 90’s
|
|
What is BISC?
The following message
circulated on On A bit of history:
BISC is an acronym for the
Berkeley Initiative in Soft Computing. My initial proposal was to refer to
the initiative as the Berkeley Soft Computing Initiative, but at the
suggestion of John Ousterhout the name was changed
to Berkeley Initiative in Soft Computing, leading to the more euphonious
acronym BISC, which rhymes with another As an idea, BISC was conceived
in October 1990, and developed in close consultation with Dean David Hodges,
EECS Chair Paul Gray, CS Associate Chair David Patterson and Director for
College Relations Marily Howekamp.
The launching of BISC was announced on March 13 at the 1991 ILP (Industrial
Liaison Program) Conference in What is soft computing?
Soft computing differs from
conventional (hard) computing in that, unlike hard computing, it is tolerant
of imprecision, uncertainty and partial truth. In effect, the role model for
soft computing is the human mind. The guiding principle of soft computing is:
Exploit the tolerance for imprecision, uncertainty and partial truth to
achieve tractability, robustness and low solution cost. The basic ideas
underlying soft computing in its current incarnation have links to many
earlier influences, among them my 1965 paper on fuzzy sets; the 1973 paper on
the analysis of complex systems and decision processes; and the 1979 report
(1981 paper) on possibility theory and soft data analysis. The inclusion of
neural network theory in soft computing came at a later point. At this
juncture, the principal constituents of soft computing (SC) are fuzzy logic
(FL), neural network theory (NN) and probabilistic reasoning (PR), with the latter
subsuming belief networks, genetic algorithms, chaos theory and parts of
learning theory. What is important to note is that SC is not a melange of FL, NN and PR. Rather,
it is a partnership in which each of the partners contributes a distinct
methodology for addressing problems in its domain. In this perspective, the
principal contributions of FL, NN and PR are complementary rather than
competitive. Implications of soft computing
The complementarity
of FL, NN and PR has an important consequence: in many cases a problem can be
solved most effectively by using FL, NN and PR in combination rather than
exclusively. A striking example of a particularly effective combination is
what has come to be known as neurofuzzy systems.
Such systems are becoming increasingly visible as consumer products ranging
from air conditioners and washing machines to photocopiers and camcorders.
Less visible but perhaps even more important are neurofuzzy
systems in industrial applications. What is particularly significant is that
in both consumer products and industrial systems, the employment of soft
computing techniques leads to systems which have high MIQ (Machine
Intelligence Quotient). In large measure, it is the high MIQ of SC-based
systems that accounts for the rapid growth in the number and variety of
applications of soft computing - and especially fuzzy logic. The conceptual structure
of soft computing suggests that students should be trained not just in neural
network theory or fuzzy logic or probabilistic reasoning but in all of the
associated methodologies, though not necessarily to the same degree. This is
the principle which guides the BISC Seminar on Soft Computing and the course
Fuzzy Logic, Neural Networks and Soft Computing which I teach at present. The
same applies to journals, books and conferences. We are beginning to see the
appearance of journals and books with soft computing in their title. A
similar trend is visible in the titles of conferences. Current status of BISC
At present, the BISC Group
- as the community is called - comprises close to 600 students, professors,
employees of private and non-private organizations and, more generally,
individuals who have interest or are active in soft computing or related
areas. A category which was initiated recently is that of the Institutional
Affiliates, which applies to universities, laboratories and non-profit
organizations. Currently, BISC has over 50 Institutional Affiliates, with
their ranks continuing to grow in number. The only qualification for
membership in BISC is interest in soft computing. A recent BISC project
aims at a compilation of references centering on various application areas.
The current areas are:
Compilation of references
is handled by an area editor and co-editors. It is expected that more topics
will be added in the near future. At The BISC Bulletin Board
(BBB) provides a mechanism for communicating information regarding employment
and postdoc availability. BBB can also be used for
other purposes. A glimpse into the future
The successful applications
of soft computing and the rapid growth of BISC suggest that the impact of
soft computing will be felt increasingly in coming years. Soft computing is
likely to play an especially important role in science and engineering, but
eventually its influence may extend much farther. In many ways, soft
computing represents a significant paradigm shift in the aims of computing -
a shift which reflects the fact that the human mind, unlike present day computers,
possesses a remarkable ability to store and process information which is
pervasively imprecise, uncertain and lacking in categoricity.
In this perspective, what is important about BISC is that it provides a
platform for the advancement of soft computing - a platform which lowers
barriers between the constituents of soft computing and facilitates
international cooperation on a global scale. Invitation
Please communicate to me
and the BISC Group any thoughts, comments or suggestions regarding BISC and/or
SC that you may have to offer. cc. Chancellor L. Tien Provost J. King Dean D. Hodges Chair D. Messerschmitt Past Chair P. Gray Associate Chair R. Wilensky Past Associate Chair D.
Patterson Associate Directors: C.
Sequin M. Tomizuka
E. Wong Director of College Relations: M. Howekamp |
|