#op3_soccer #deepmind #robots
Courtesy : @OP3Soccer @Google_DeepMind
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DeepMind, scientists have successfully trained low-cost humanoid robots to play 1v1 soccer. Using advanced techniques like deep reinforcement learning, the team was able to teach these robots agile skills and tactics, bringing us one step closer to having robots perform complex tasks in the real world.
The training process involved two stages, where robots first learned independent skills like getting up from the ground and scoring goals. In the second stage, these skills were combined into a single soccer-playing agent, which improved its tactics through self-play against previous versions of itself.
This progress could lead to the development of advanced humanoid robots capable of performing complex tasks across various industries, such as assisting in disaster relief efforts or navigating intricate environments for search and rescue missions. Additionally, the study explores the potential of multi-agent settings, where robots could collaborate and coordinate more effectively.
The team believes that their proposed method could be applied to more complex settings, such as training agents in teams of two or more players. In preliminary experiments with 2v2 soccer, the agents demonstrated promising results, learning division of labor and simple forms of collaboration.
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