Title :
Towards the verification and validation of online learning systems: general framework and applications
Author :
Mili, Ali ; Jiang, GuangJie ; Cukic, Bojan ; Liu, Yan ; Ayed, R.B.
Author_Institution :
New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
Online adaptive systems cannot be certified using traditional testing and proving methods, because these methods rely on assumptions that do not hold for such systems. In this paper, we discuss a framework for reasoning about online adaptive systems, and see how this framework can be used to perform the verification of these systems. In addition to the framework, we present some preliminary results on concrete neural network models.
Keywords :
computer aided instruction; formal verification; multilayer perceptrons; radial basis function networks; reasoning about programs; MLP neural networks; RBF neural networks; adaptive control; formal methods; neural network models; online adaptive systems; online learning systems; radial basis functions; refinement calculi; system validation; system verification; Adaptive control; Adaptive systems; Aerodynamics; Aerospace control; Control systems; Fault tolerant systems; Intelligent sensors; Learning systems; Neural networks; Programmable control;
Conference_Titel :
System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on
Print_ISBN :
0-7695-2056-1
DOI :
10.1109/HICSS.2004.1265713
