Continual Reinforcement Learning with Multi-Timescale Replay

Kaplanis Christos
Kaplanis Christos
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Abstract:

In this paper, we propose a multi-timescale replay (MTR) buffer for improving continual learning in RL agents faced with environments that are changing continuously over time at timescales that are unknown to the agent. The basic MTR buffer comprises a cascade of sub-buffers that accumulate experiences at different timescales, enabling ...More

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