Actor-Critic

A reinforcement learning architecture combining two components: an actor that decides which actions to take, and a critic that evaluates how good those actions were. The critic's feedback shapes the actor's learning over time, making the combination more stable and sample-efficient than either approach on its own. See also: Policy Gradient, Reward Model.