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N-Version Genetic Programming via Fault Masking
| Book Series | Lecture Notes in Computer Science |
| Publisher | Springer Berlin / Heidelberg |
| ISSN | 0302-9743 (Print) 1611-3349 (Online) |
| Volume | Volume 2278/2002 |
| Book | Genetic Programming |
| DOI | 10.1007/3-540-45984-7 |
| Copyright | 2002 |
| ISBN | 978-3-540-43378-1 |
| DOI | 10.1007/3-540-45984-7_17 |
| Pages | 172-181 |
| Subject Collection | Computer Science |
| SpringerLink Date | Tuesday, January 01, 2002 |
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N-Version Genetic Programming via Fault Masking
Kosuke Imamura9 , Heckendorn Robert B. 9 , Terence Soule9 and Foster James A. 9 
| (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.
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