WOGAN at the SBST 2022 CPS Tool Competition
Jarkko Peltom\"aki, Frankie Spencer, Ivan Porres
TL;DR
WOGAN is an online test generation algorithm utilizing Wasserstein GANs, evaluated in the SBST 2022 CPS tool competition for self-driving car AI, demonstrating its effectiveness in automated testing.
Contribution
This paper introduces WOGAN, a novel online test generation method based on Wasserstein GANs, applied to autonomous vehicle AI testing.
Findings
WOGAN performed competitively in the SBST 2022 CPS tool competition.
WOGAN effectively generates tests for self-driving car AI.
The approach demonstrates the potential of GANs in automated testing.
Abstract
WOGAN is an online test generation algorithm based on Wasserstein generative adversarial networks. In this note, we present how WOGAN works and summarize its performance in the SBST 2022 CPS tool competition concerning the AI of a self-driving car.
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Taxonomy
TopicsAdversarial Robustness in Machine Learning · Advanced Neural Network Applications · Handwritten Text Recognition Techniques