What is the Bellman equation in reinforcement learning?
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The Bellman equation is a recursive equation that expresses the value of a state or state-action pair in terms of the immediate reward and the value of the next state (or next state-action pair).
The Bellman equation in reinforcement learning relates the value of a state to the expected immediate reward and the value of the next state under a given policy. It is represented as \( V(s) = \mathbb{E}_\pi \left[ R_{t+1} + \gamma V(S_{t+1}) \right] \).