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In autonomous driving systems, the iterative neuro-symbolic architecture uses a neural network to detect traffic signs from real-time images, while a symbolic reasoning engine evaluates these detections against contextual rules, such as verifying if a stop sign is logically positioned near an intersection, and prompts the neural network to re-evaluate if inconsistencies are found.

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