N-Version Genetic Programming via Fault Masking
作者： Kosuke Imamura , Robert B. Heckendorn , Terence Soule , James A. Foster
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摘要: We introduce a new method, N-Version Genetic Programming (NVGP), for building fault tolerant software by an ensemble of automatically generated modules in such way as to maximize their collective masking ability. The itself is example n-version modular redundancy tolerance, where the output most frequent n independent modules. By maximizing masking, NVGP approaches tolerance expected from version with faults component comprises individual large pool genetic programming, using operators that increase diversity population. Our experimental test problem classified promoter regions Escherichia coli DNA sequences. For this problem, reduced number and variance errors over single produced GP, statistical significance.
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