Abstract
Human-robot interaction (HRI) is a rapidly advancing field with neural networks playing a central role in making robots more capable of understanding and responding to human behavior. By leveraging deep learning algorithms, robots can now recognize and interpret human emotions, gestures, and speech with increasing accuracy. This article explores the future potential of neural networks in HRI, focusing on how these technologies will enhance robots' social intelligence, adaptability, and real-time decision-making. We also discuss the challenges of implementing neural networks in real-world HRI applications and consider the ethical and societal implications of increasingly autonomous robots.
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