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Arxiv
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A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control
- Deep reinforcement learning for continuous control has made significant progress, but current methods often suffer from primacy bias.
- A new algorithm called Forget and Grow (FoG) is proposed to address this issue by incorporating mechanisms inspired by neuroscience.
- FoG includes Experience Replay Decay (ER Decay) to forget early experiences and Network Expansion to grow neural capacity.
- Empirical results on various continuous control benchmarks show that FoG outperforms existing deep RL algorithms like BRO, SimBa, and TD-MPC2.
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