AINeutralarXiv – CS AI · 8h ago6/10
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Position: Deployed Reinforcement Learning should be Continual
A position paper argues that deployed reinforcement learning systems should adopt continual learning rather than the traditional train-then-fix approach. The authors identify four sources of non-stationarity in deployed environments that require agents to continuously adapt and learn, challenging the current industry paradigm where agents remain static until performance degradation necessitates retraining.