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Test and Evaluation by Genetic Algorithms
October 1993 (vol. 8 no. 5)
pp. 9-14

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.

Citation:
Alan C. Schultz, John J. Grefenstette, Kenneth A. De Jong, "Test and Evaluation by Genetic Algorithms," IEEE Intelligent Systems, vol. 8, no. 5, pp. 9-14, Oct. 1993, doi:10.1109/64.236476
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