AIBullisharXiv – CS AI · Mar 57/10
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Self-adapting Robotic Agents through Online Continual Reinforcement Learning with World Model Feedback
Researchers have developed a new framework for robotic agents that can adapt and learn continuously during operation, rather than being limited to fixed parameters from offline training. The system uses world model prediction residuals to detect unexpected events and automatically trigger self-improvement without external supervision.