Behavioral Cloning Outperforms Entropy-Regularized RL: Critic-Driven Failure of Actor-Critic Methods on Adaptive Tumor Treatment
Adaptive dosing requires policies that reduce tumor burden without excessive toxicity. Learned dosing policies are typically judged against historical or heuristic comparators, which cannot show whether a policy has found the best behavior available. We instead study a three-population tumor-control ODE in which optimal-control analysis fixes the form of a good schedule -- bang-bang dosing punctuated by a singular arc -- and construct a numerical controller of that form as a proxy for near-optimal behavior. Judged against this reference under a sustained-cure criterion -- 200 consecutive days below 5% carrying capacity -- Soft Actor-Critic (SAC) trained from scratch never reaches cure. Be...
| Authors | Aleksandar Dimitrov, Giacomo Spigler |
|---|---|
| Primary category | cs.LG |
| Published | 6 September 2026 |
| Last updated at source | 6 September 2026 |
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