AIBullisharXiv – CS AI · 6h ago6/10
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Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation
Researchers propose Incremental Residual Reinforcement Learning (IRRL), a new method that enables mobile robots to learn social navigation directly in physical environments without requiring large computational resources or replay buffers. The approach combines incremental learning with residual reinforcement learning to improve efficiency, achieving performance comparable to traditional methods while enabling real-world adaptation.