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Artificial Neural Networks (ANNs) are interconnected layers of nodes, or "neurons," designed to simulate the human brain's problem-solving abilities. They are a key component of Deep Learning and Artificial Intelligence. In the context of Expert Systems, ANNs can be used to model complex decision-making processes, enhancing the system's capability to learn from experience, adapt to new inputs, and make accurate predictions. By continuously adjusting the weights of connections between neurons based on input data, ANNs enable Expert Systems to improve their performance and accuracy over time. This learning process is fundamental to Deep Learning, where ANNs with multiple hidden layers are employed to tackle increasingly intricate tasks in areas such as computer vision, natural language processing, and speech recognition. Overall, ANNs serve as a powerful tool for optimizing Expert Systems' decision-making capabilities by integrating advanced learning algorithms within their structure.