Understanding Reinforcement Learning with Neural Networks Part 2: Why Backpropagation Is Not Enough

Reinforcement learning requires a different approach to training neural networks because it lacks predefined ideal output values, making standard backpropagation ineffective. Policy gradients offer a solution by estimating derivatives through guessed ideal outputs, crucial for developers working on AI systems that need to learn from rewards and punishments rather than labeled data.

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