Episode 47 – Deep Reinforcement Learning
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Episode 47 – Deep Reinforcement Learning
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About this listen
Reinforcement learning (RL) has always been about trial and error—but with deep learning, RL reached new heights. This episode explains how agents like DQN learned to play Atari games directly from pixels and how policy gradient methods advanced robotics and decision-making. We’ll also discuss the limitations of deep RL—its brittleness, sample inefficiency, and ethical concerns—and why it remains both one of AI’s most powerful and most challenging frontiers.
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