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Test and evaluation by genetic algorithms

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3 Author(s)
A. C. Schultz ; US Naval Res. Lab., Washington, DC, USA ; J. J. Grefenstette ; K. A. De Jong

A machine learning technique for automating the traditional controller tests process that evaluates autonomous-vehicle software controllers is discussed. In the proposed technique, a controller is subjected to an adaptively chosen set of fault scenarios in a vehicle simulator, and then a genetic algorithm is used to search for fault combinations that produce noteworthy actions in the controller. This approach has been applied to find a minimal set of faults that produces degraded vehicle performance and a maximal set of faults that can be tolerated without significant performance loss.<>

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IEEE Expert  (Volume:8 ,  Issue: 5 )