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TD3+BC — the simplest offline RL baseline.

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Answer

  • Fujimoto & Gu 2021.
  • TD3 (actor-critic) + BC (behavior cloning) regularizer added to policy loss: min E[-Q(s, π(s))] + λ (π(s)    adata)2({\pi}(s)\; - \;a_{\mathrm{data}})^{2}.
  • Encourages policy to stay close to data actions.
  • Extremely simple (add one term), strong performance on D4RL.
  • Foundation demonstrating that a small BC regularization is often enough for offline RL — sophisticated methods (CQL, IQL) add marginal gains.
Check yourself — multiple choice
  • Random
  • TD3 + BC regularizer λ (π(s)    adata)2({\pi}(s)\; - \;a_{\mathrm{data}})^{2} added to policy loss; extremely simple + strong D4RL performance; showed a small BC term is often enough
  • Same as SAC
  • Not real

TD3+BC: add BC term to TD3 loss; simplest strong offline RL baseline.

#offline-rl

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