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N-Version Genetic Programming via Fault Masking

Kosuke ImamuraContact Information, Heckendorn Robert B. Contact Information, Terence SouleContact Information and Foster James A. Contact Information

(9)  Initiative for Bioinformatics and Evolutionary Studies (IBEST), Dept. of Computer Science, University of Idaho, 83844-1010 Moscow, ID
Abstract
We introduce a new method, N-Version Genetic Programming (NVGP), for building fault tolerant software by building an ensemble of automatically generated modules in such a way as to maximize their collective fault masking ability. The ensemble itself is an example of n-version modular redundancy for fault tolerance, where the output of the ensemble is the most frequent output of n independent modules. By maximizing collective fault masking, NVGP approaches the fault tolerance expected from n version modular redundancy with independent faults in component modules. The ensemble comprises individual modules from a large pool generated with genetic programming, using operators that increase the diversity of the population. Our experimental test problem classified promoter regions in Escherichia coli DNA sequences. For this problem, NVGP reduced the number and variance of errors over single modules produced by GP, with statistical significance.

Contact Information Kosuke Imamura
Email: kosuke@cs.uidaho.edu
URL: http://www.cs.uidaho.edu/ibest

Contact Information Heckendorn Robert B.
Email: heckendo@cs.uidaho.edu

Contact Information Terence Soule
Email: tsoule@cs.uidaho.edu

Contact Information Foster James A.
Email: foster@cs.uidaho.edu
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