Android Coach improves online agent training efficiency by enabling multiple actions per state via a critic-based coach, process reward model, and group-wise advantage estimation, delivering 7.5-8.3% success rate gains and 1.4x efficiency over PPO/GRPO baselines.
Thus, the expectation of our estimator is the true policy gradient: E[gi] =∇ θJ(θ)−0 =∇ θJ(θ) This proves the estimator isunbiased
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Android Coach: Improve Online Agentic Training Efficiency with Single State Multiple Actions
Android Coach improves online agent training efficiency by enabling multiple actions per state via a critic-based coach, process reward model, and group-wise advantage estimation, delivering 7.5-8.3% success rate gains and 1.4x efficiency over PPO/GRPO baselines.