CfP Special Issue "Neural Networks and Structured Knowledge"
Franz Kurfess
franz at homer.njit.edu
Mon Mar 9 18:46:44 EST 1998
Special Issue "Neural Networks and Structured Knowledge"
in Applied Intelligence:
The International Journal of Artificial Intelligence,
Neural Networks, and Complex Problem-Solving Techniques
Call for Contributions
The submission of papers is invited for a special issue on
"Neural Networks and Structured Knowledge" of the Applied
Intelligence Journal.
Issue Theme
The representation and processing of knowledge in computers traditionally
has been concentrated on symbol-oriented approaches, where knowledge items
are associated with symbols. These symbols are grouped into structures,
reflecting the important relationships between the knowledge items.
Processing of knowledge then consists of manipulation of the symbolic
structures, and the result of the manipulations can be interpreted
by the user. Whereas this approach has seen some remarkable successes,
there are also domains and problems where it does not seem adequate.
Some of the problems are computational complexity,
rigidity of the representation, the difficulty of reconciling
the artificial model with the real world, the integration
of learning into the model, and the treatment of incomplete
or uncertain knowledge.
Neural networks, on the other hand, have advantages that make them good
candidates for overcoming some of the above problems.
Whereas approaches to use
neural networks for the representation and processing of structured knowledge
have been around for quite some time, especially in the area of
connectionism, they frequently suffer from problems with expressiveness,
knowledge acquisition, adaptivity and learning, or human interpretation.
In the last years much progress has been made in the theoretical
understanding and the construction of neural systems capable of representing
and processing structured knowledge in an adequate way, while maintaining
essential capabilities of neural networks such as learning, tolerance
of noise, treatment of inconsistencies, and parallel operation.
The theme of this special issue comprises
* the investigation of the underlying theorecical foundations,
* the implementation and evaluation of methods for representation
and processing of structured knowledge with neural networks, and
* applications of such approaches in various domains.
Topics of Interest
The list below gives some examples of intended topics.
* Concepts and Methods:
o extraction, injection and refinement of structured knowledge
from, into and by neural networks
o inductive discovery/formation of structured knowledge
o combining symbolic machine learning techniques with neural lerning
paradigms to improve performance
o classification, recognition, prediction, matching
and manipulation of structured information
o neural methods that use or discover structural similarities
o neural models to infer hierachical categories
o structuring of network architectures: methods for introducing
coarse-grained structure into networks, unsupervised learning of
internal modularity
* Application Areas:
o medical and technical diagnosis:
discovery and manipulation of structured dependencies,
constraints, explanations
o molecular biology and chemistry:
prediction of molecular structure unfolding,
classification of chemical structures, DNA analysis
o automated reasoning:
robust matching, manipulation of logical terms,
proof plans, search space reduction
o software engineering:
quality testing, modularisation of software
o geometrical and spatial reasoning:
robotics, structured representation of objects in space,
figure animation, layouting of objects
o other applications that use, generate or manipulate
structures with neural methods: strucures in music composition, legal
reasoning, architectures, technical configuration, ...
The central theme of this issue will be the treatment of structured
information using neural networks, independent of the particular network type or
processing paradigm. Thus the theme is orthogonal to the question of
connectionist/symbolic integration, and is not intended as a continuation
of the more philosphically oriented discussion of symbolic vs. subsymbolic
representation and processing.
Submission Process
Prospective authors should send an electronic mail message indicating
their intent to submit a paper to the guest editor
of the special issue, Franz J. Kurfess (kurfess at cis.njit.edu).
This message should contain a preliminary abstract and three to five
keywords.
Six hard copies of the final manuscript should be sent to
the guest editor (not to the Applied Intelligence Editorial office):
Prof. Franz J. Kurfess
New Jersey Institute of Technology Phone: (973) 596 5767
Department of Computer and Information Science Fax: (973) 596 5777
University Heights Email: kurfess at cis.njit.edu
Newark, NJ 07102-1982 WWW: http://www.cis.njit.edu/~franz
To speed up the reviewing process, authors should also send a PostScript
version of the paper via email to the guest editor.
Prospective authors can find further information about the journal on
the home page
http://kapis.www.wkap.nl/journalhome.htm/0924-669X
Schedule
Paper submission deadline: May 1, 1998
Review decision by: July 31, 1998
Final manuscript due: August 31, 1998
Tentative publication date: November 1998
More information about the Connectionists
mailing list