stability-plasticity-dilemma

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papersTODAY 04:00 UTC

Continual DQN Expansion with Curriculum Learning for Adaptive Train Scheduling

A new arXiv paper tackles the stability-plasticity dilemma in continual reinforcement learning by progressively expanding a DQN agent guided by a curriculum. The approach is applied to adaptive train scheduling, where conditions shift over time and earlier knowledge must be retained. It aims to let the agent grow more complex behaviors without overwriting what it already learned.

reinforcement-learning/continual-learning/scheduling/research