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Scientists have developed a scalable reinforcement learning framework for humanoid robots, enhancing their adaptability and efficiency in executing complex tasks with human guidance. This innovative approach utilizes reinforcement learning algorithms to provide robots with a greater level of autonomy, improving their motor functions and decision-making capabilities over time. This development has significant implications for the robotics industry and raises important discussions on ethical considerations and technical challenges.
