Advantage Actor-Critic (A2C) is a reinforcement learning algorithm that improves upon the basic Actor-Critic method by using multiple parallel actors to gather experiences. This approach helps to decorrelate the data, leading to more stable and efficient training. A2C is particularly effective in environments where exploration is challenging and rewards are sparse. AI
Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →
RANK_REASON The item describes a reinforcement learning algorithm, which falls under research.