+**A3C** (Asynchronous Advantage Actor-Critic) is a fundamental algorithm in [Reinforcement Learning](/wiki/reinforcement_learning), designed to train artificial agents efficiently. It employs multiple worker agents to explore diverse environment copies in parallel, asynchronously updating a shared [Neural Network](/wiki/neural_network). This parallel, decentralized approach often leads to faster and more stable learning outcomes.
+## See also
+- [Deep Learning](/wiki/deep_learning)
+- [Machine Learning](/wiki/machine_learning)
+- [Actor-Critic](/wiki/actor-critic)
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