Connectionists: Call for papers - reminder

[pramod gupta]

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Verification, Validation and Certification of Neuro-Adaptive Controllers in 
Safety-Related Areas
Montreal, Canada, Friday, August 5, 2005

A Workshop in conjunction with the International Joint Conference on Neural 
Networks 2005

Workshop Outline

Over the recent years, artificial Neural Networks (NNs) have found their way 
into various safety-related and safety-critical areas, like transportation, 
avionics, environmental monitoring and control, and medical 
applications.Quite often, these applications (using NN techniques ranging 
from classification to monitoring and control) proved to be highly 
successful, leading from a pure research prototype into a serious 
experimental system (e.g., a neural-network-based flight-control system 
test-flown on a manned NASA F-15 aircraft) or a commercial product (e.g., 
Sharp's Logi-cook).
However, the general question of how to make sure that the NN-based adaptive 
control system performs as expected in all cases has not yet been addressed 
satisfactorily. While theory and concepts of adaptive systems and 
intelligent control have been studied in depth over the past decade or so, 
only very little attention has been paid to the issue of validating the 
correctness and safety of their operation. All safety-related software 
applications require careful verification and validation (V\&V) of the 
software components, ranging from extended testing to full-fledged 
certification procedures (e.g., DO178-B). The adaptive nature of neural 
networks requires a significantly different approach to verification and 
validation than used for traditional software, since dynamic adaptation of 
parameters, iterative numerical algorithms, and complex control 
architectures renders traditional approaches to V\&V impracticable. Many 
prototypical/experimental application of neural networks in safety-related 
areas have demonstrated superior behavior and practical usefulness. Unless, 
however, methods and techniques have been developed which are capable of 
assuring the correctness and performance of a neural-network based system, 
NN applicability in safety-critical areas is substantially limited.

The purpose of the workshop is to bring together researchers and users of 
learning and adaptive systems and control systems in order to create a forum 
for discussing recent advances in verification, validation, and testing of 
learning systems, to understand better the practical requirements for 
developing and deploying neuro-adaptive, and to inspire research on new 
methods and techniques for verification, validation, and testing.


Topics of Interest

Topics of interest include but are not limited to:

applications of learing and adaptive methods and NNs in safety-critical 
areas and experience/lessons learned.
applications of collaborative filtering problems, node modeling for belief 
networks and dependency networks, sequential decision making tasks, 
diagnosis problems, autonomous systems, robotics, and security, etc.
techniques, tools, and methods to assess and guarantee the performance of a 
NN, e.g., statistical (Bayesian) methods, rule extraction with subsequent  
V&V, methods for convergence/stability analysis, dynamic monitoring of the 
NN behavior, etc.,
V&V techniques that are specifically suitable for on-line trained and 
adaptive systems, and
software development, V\&V, and certification processes for learning and 
adaptive systems.


Important Dates:
Authors should submit a PDF file of their paper to schumann AT 
email.arc.nasa.gov

Submission of papers:                April 27,  2005
Notification of acceptance:         May 4, 2005
Camera-ready copy:                   May 15, 2005
Workshop:                                 August 5, 2005


Workshop organizers
Johann Schumann, RIACS/NASA Ames, schumann AT email.arc.nasa.gov 
(650)604-0941
Pramod Gupta, QSS Inc/ NASA Ames, pgupta AT email.arc.nasa.gov (650)604-1824
Dragos Margineantu, The Boeing Company, dragos.d.margineantu AT boeing.com

Program Committee

B. Cukic, WVU
S. Jacklin, NASA Ames
T. Menzies, PSU
A. Mili, NJIT
M. Richard, NASA DFRC
F. Sheldon, ORNL

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For questions or comments, please send email to schumann AT 
email.arc.nasa.gov