How do Policy Gradient Methods differ from value-based methods in their approach to reinforcement learning?
- Value-based methods learn
- They learn both the
- Policy Gradient Methods
- They learn neither
Policy Gradient Methods focus on learning the policy directly, which means they determine the probability of taking actions. Value-based methods, on the other hand, learn the value of states or state-action pairs. This key difference is essential for understanding the approach to RL each method takes.
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