By Swift, Society for Worldwide Interban
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Additional info for Adaptive Intelligent Systems. Proceedings of the Bankai Workshop, Brussels, Belgium, 12–14 October 1992
Sophistication. Is the environment that we work in for neural networks sophisticated enough to guarantee that it belongs today in technology? What would make something sophisticated? Are there good environments in which we can work? We have implemental compilation today, available in the neural network area; we have symbolic de-buggers; we have graphical user interfaces; we have editors. We have de-bugging facilities. There is, for instance, a visual display of weights using Hinton's diagrams that will be very useful.
What would make something sophisticated? Are there good environments in which we can work? We have implemental compilation today, available in the neural network area; we have symbolic de-buggers; we have graphical user interfaces; we have editors. We have de-bugging facilities. There is, for instance, a visual display of weights using Hinton's diagrams that will be very useful. We have hidden unit activity patterns and we have sensitivity analysis of individual hidden units. These are all concepts that are very important in de-bugging a neural network programme, and we have them today.
They learned the precious value of rapidly repeating cycles of user feedback and involvement as they progressed in their development. Some tools and techniques emerged to support these new practices. Rule-based systems are a common example of tools found effective to support this activity. Knowledge Engineering principles emerged to guide developers in applying these ideas. In essence, they focussed on means to involve users very early and continually as a project evolved. Developers needed to be equipped to modify rapidly their products and adapt to the growth in understanding of the real needs and solutions.