AIBullisharXiv – CS AI · Jun 237/10
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AdaReP:Adaptive Re-Planning under Model Mismatch for Neural World-Model Predictive Control
AdaReP is a training-free algorithm that optimizes neural world-model predictive control by dynamically deciding when to replan versus reusing cached plans. By analyzing prediction mismatch propagation through local dynamics, the method achieves over 80% reduction in computational queries while maintaining task performance across simulated and real robotic manipulation tasks.