RL Part 14: Baselines, Advantage Function, and Actor-Critic
ShawnHymel · x · 2026-08-20
Part 14 of the Reinforcement Learning math series covers how subtracting a baseline from the return reduces variance, leading to the Advantage Function. It reintroduces bootstrapping to handle continuing tasks and culminates in the Actor-Critic architecture, the cornerstone of modern RL algorithms. The post explains the limitations of REINFORCE and the math behind variance reduction.
Related event: RL Math Series Part 14: Baselines, Advantage Functions and Actor-Critic(2 posts)→
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